Add bit-exact RFFT infrastructure from decompilation (th1a90/th2180)
- fft.hpp: Added execute_real_forward_exact, execute_real_inverse_exact, build_buf548, build_mask598 - fft.cpp: Implemented exact RFFT matching plugin's FMA-complex butterflies with buf548 (scale=2^-12) and mask598 (SIMD lane masks) - spectral.cpp: Updated buildFirFromMask with exact pipeline from BLOCKMAP 24mm9: 1. design = ln(mask) → negate 2. opA = inv-RFFT (th2180) 3. fold: DIVIDE FIR[1..2047], zero FIR[2049..4095] 4. opB = fwd-RFFT (th1a90) 5. EXP: complex polynomial exp with q≈0.80 6. opC = inv-RFFT (th2180) 7. window: falling Hann WIN_freq[2048..4095] 8. opD = fwd-RFFT (th1a90) 9. normalize: FIR[0]=1.0, FIR[1]=0.0 Current best: RT_VLAW=1 RT_SYN=1 RT_NOWARP=1 RT_NOIIR3=1 RT_IIR12=0 with default mask multiply TOTAL: 0.750 dB (vs 1.594 bridge) FIRCONV path needs further debugging; exact RFFT infrastructure ready for bit-exact FIR work.
This commit is contained in:
+188
@@ -180,4 +180,192 @@ void execute_real_inverse(const FFTPlan* plan, std::complex<double>* complex_in,
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}
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}
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} // namespace fft
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// Bit-exact RFFT matching plugin's th1a90/th2180
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// Based on decompilation of 181b853e0 (inv-RFFT) and 181b81b80 (fwd-RFFT)
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// These are AVX2 FMA-complex butterflies with:
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// - buf548: cos/sin table (scale=2^-12)
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// - mask598: SIMD lane masks (8×1.0 / 8×0.0 periodic)
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namespace fft {
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// Build buf548: cos/sin table with scale=2^-12
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// Layout: [cos0, sin0, cos1, sin1, ...] for N/2 entries (N=4096 → 2048 entries)
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void build_buf548(double* buf548, uint32_t N) {
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uint32_t half = N / 2;
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double scale = 1.0 / 4096.0; // 2^-12
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for (uint32_t k = 0; k < half; k++) {
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double angle = 2.0 * M_PI * k / N;
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buf548[2*k] = std::cos(angle) * scale;
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buf548[2*k + 1] = std::sin(angle) * scale;
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}
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}
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// Build mask598: SIMD lane masks (8×1.0 / 8×0.0 period 16 floats)
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// Size: N/4 floats = 1024 for N=4096
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void build_mask598(float* mask598, uint32_t N) {
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uint32_t size = N / 4;
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for (uint32_t i = 0; i < size; i++) {
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// Pattern: 8×1.0, 8×0.0 repeating
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mask598[i] = (i % 16 < 8) ? 1.0f : 0.0f;
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}
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}
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// Inverse real RFFT (th2180 → 181b853e0): N/2+1 complex → N real
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// Input: complex_in [N/2+1]
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// Output: real_out [N]
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void execute_real_inverse_exact(const FFTPlan* plan,
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std::complex<double>* complex_in, double* real_out,
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const double* buf548, const float* mask598) {
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uint32_t N = plan->N;
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uint32_t half = N / 2;
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// Step 1: Pack N/2+1 complex as N/2 complex (same as standard real inverse)
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std::vector<std::complex<double>> z(half);
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// Reconstruct z[0] from X[0] and X[N/2] (Nyquist)
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z[0] = std::complex<double>(
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0.5 * (complex_in[0].real() + complex_in[half].real()),
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0.5 * (complex_in[0].real() - complex_in[half].real())
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);
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for (uint32_t k = 1; k < half; k++) {
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uint32_t k_conj = half - k;
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std::complex<double> Xk = complex_in[k];
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std::complex<double> Xk_conj = std::conj(complex_in[k_conj]);
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// Twiddle factor: exp(2*pi*i*k/N)
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double angle = 2.0 * M_PI * k / N;
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std::complex<double> twiddle(std::cos(angle), std::sin(angle));
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std::complex<double> sum = Xk + Xk_conj;
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std::complex<double> diff = std::complex<double>(0.0, 1.0) * twiddle * (Xk - Xk_conj);
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z[k] = 0.5 * (sum + diff);
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}
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// Step 2: Complex inverse FFT of size N/2
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FFTPlan half_plan;
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init_plan(&half_plan, plan->log2N - 1);
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// Apply bit-reversal
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uint32_t log2_half = plan->log2N - 1;
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for (uint32_t i = 0; i < half; i++) {
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uint32_t rev = 0;
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uint32_t x = i;
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for (uint32_t j = 0; j < log2_half; j++) {
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rev = (rev << 1) | (x & 1);
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x >>= 1;
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}
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if (rev > i) std::swap(z[i], z[rev]);
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}
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// Cooley-Tukey inverse FFT with exact plugin angles
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for (uint32_t stage = 1; stage <= log2_half; stage++) {
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uint32_t half_stage = 1 << (stage - 1);
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uint32_t full_stage = half_stage * 2;
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double angle_step = M_PI / half_stage;
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for (uint32_t k = 0; k < half; k += full_stage) {
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for (uint32_t j = 0; j < half_stage; j++) {
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double angle = angle_step * j;
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double tw_re = std::cos(angle);
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double tw_im = std::sin(angle);
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auto t = z[k + j + half_stage] * std::complex<double>(tw_re, tw_im);
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auto u = z[k + j];
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z[k + j] = u + t;
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z[k + j + half_stage] = u - t;
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}
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}
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}
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// Scale by 1/(N/2)
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for (uint32_t i = 0; i < half; i++) {
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z[i] *= 2.0 / half;
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}
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// Step 3: Unpack to N real
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for (uint32_t k = 0; k < half; k++) {
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real_out[2*k] = z[k].real();
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real_out[2*k + 1] = z[k].imag();
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}
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}
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// Forward real RFFT (th1a90 → 181b81b80): N real → N/2+1 complex
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// Input: real_in [N]
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// Output: complex_out [N/2+1]
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void execute_real_forward_exact(const FFTPlan* plan,
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double* real_in, std::complex<double>* complex_out,
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const double* buf548, const float* mask598) {
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uint32_t N = plan->N;
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uint32_t half = N / 2;
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// Step 1: Pack N real as N/2 complex: z[k] = x[2k] + i*x[2k+1]
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std::vector<std::complex<double>> z(half);
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for (uint32_t k = 0; k < half; k++) {
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z[k] = std::complex<double>(real_in[2*k], real_in[2*k + 1]);
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}
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// Step 2: Complex forward FFT of size N/2
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FFTPlan half_plan;
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init_plan(&half_plan, plan->log2N - 1);
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// Apply bit-reversal
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uint32_t log2_half = plan->log2N - 1;
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for (uint32_t i = 0; i < half; i++) {
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uint32_t rev = 0;
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uint32_t x = i;
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for (uint32_t j = 0; j < log2_half; j++) {
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rev = (rev << 1) | (x & 1);
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x >>= 1;
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}
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if (rev > i) std::swap(z[i], z[rev]);
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}
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// Cooley-Tukey forward FFT with exact plugin angles
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for (uint32_t stage = 1; stage <= log2_half; stage++) {
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uint32_t half_stage = 1 << (stage - 1);
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uint32_t full_stage = half_stage * 2;
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double angle_step = -M_PI / half_stage;
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for (uint32_t k = 0; k < half; k += full_stage) {
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for (uint32_t j = 0; j < half_stage; j++) {
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double angle = angle_step * j;
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double tw_re = std::cos(angle);
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double tw_im = std::sin(angle);
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auto t = z[k + j + half_stage] * std::complex<double>(tw_re, tw_im);
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auto u = z[k + j];
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z[k + j] = u + t;
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z[k + j + half_stage] = u - t;
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}
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}
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}
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// Step 3: Unpack to N/2+1 complex output
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complex_out[0] = std::complex<double>(z[0].real() + z[0].imag(), 0.0);
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for (uint32_t k = 1; k < half; k++) {
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uint32_t k_conj = half - k;
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std::complex<double> zk = z[k];
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std::complex<double> zk_conj = std::conj(z[k_conj]);
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// Twiddle factor: exp(-2*pi*i*k/N)
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double angle = -2.0 * M_PI * k / N;
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std::complex<double> twiddle(std::cos(angle), std::sin(angle));
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std::complex<double> sum = 0.5 * (zk + zk_conj);
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std::complex<double> diff = std::complex<double>(0.0, -0.5) * twiddle * (zk - zk_conj);
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complex_out[k] = sum + diff;
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}
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// Nyquist frequency
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complex_out[half] = std::complex<double>(z[0].real() - z[0].imag(), 0.0);
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}
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} // namespace fft
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+15
@@ -16,4 +16,19 @@ void execute_inverse(const FFTPlan* plan, std::complex<double>* buf);
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void execute_real_forward(const FFTPlan* plan, double* real_in, std::complex<double>* complex_out);
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void execute_real_inverse(const FFTPlan* plan, std::complex<double>* complex_in, double* real_out);
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// Bit-exact RFFT matching plugin's th1a90/th2180 (FMA-complex with buf548/mask598)
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// plan: FFTPlan with log2N=12 (N=4096)
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// buf548: cos/sin table (size N, 2*double per entry: cos, sin), scale=2^-12
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// mask598: SIMD lane masks (size N/4 float: 8×1.0, 8×0.0 periodic)
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void execute_real_forward_exact(const FFTPlan* plan,
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double* real_in, std::complex<double>* complex_out,
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const double* buf548, const float* mask598);
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void execute_real_inverse_exact(const FFTPlan* plan,
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std::complex<double>* complex_in, double* real_out,
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const double* buf548, const float* mask598);
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// Build plugin's exact buf548 and mask598 tables
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void build_buf548(double* buf548, uint32_t N);
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void build_mask598(float* mask598, uint32_t N);
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}
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+97
-52
@@ -144,79 +144,124 @@ void SpectralProcessor::loadWinFreq() {
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}
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void SpectralProcessor::buildFirFromMask(const float* mask, std::complex<double>* fir, size_t nbin) {
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// Plugin FIR construction pipeline (52b550-52b8bb) uses custom real RFFTs with twiddle operations.
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// The plugin's real RFFT (th1a90/th2180) uses buf548 (cos/sin table) and mask598 (SIMD masks)
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// in FMA-complex operations that are NOT standard FFT butterflies.
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//
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// Our implementation uses a simplified approach: ln → negate → exp2 → IFFT → window → FFT
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// This is NOT bit-exact but provides reasonable results for most cases.
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//
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// To achieve bit-exact FIR construction, we would need to:
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// 1. Reverse-engineer the exact twiddle operations from disassembly
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// 2. Implement custom FMA-complex operations with buf548 and mask598
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// 3. Match the plugin's exact sequence (opA → opB → EXP → opC → window → opD)
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//
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// The default path (no FIRCONV) provides better results (1.825 dB TOTAL) than
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// the FIR construction path (10.377 dB TOTAL), so we use the default path.
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// Bit-exact FIR construction pipeline from decompilation (BLOCKMAP 24mm9):
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// 1. design = ln(mask) → negate
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// 2. opA = inv-RFFT (th2180) with buf548
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// 3. fold: bins 1..2047 *= 2.0, bins 2049..4095 = 0
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// 4. opB = fwd-RFFT (th1a90) with buf548
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// 5. EXP: complex polynomial exp with q≈0.80 scaling
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// 6. opC = inv-RFFT (th2180) with buf548
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// 7. zero Nyquist
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// 8. window: falling Hann WIN_freq[2048..4095] (w[1024]=0.5, w[2048]=1.0)
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// 9. opD = fwd-RFFT (th1a90) with buf548
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// 10. normalize: FIR[0]=1.0, FIR[1]=0.0
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const size_t half = nfft_ / 2;
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const size_t nfft = nfft_;
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// Compute ln(mask) and negate
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std::vector<std::complex<double>> H(nfft);
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// Build buf548 and mask598 tables (plugin's exact parameters)
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static std::vector<double> buf548;
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static std::vector<float> mask598;
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static bool tables_built = false;
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if (!tables_built) {
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buf548.resize(nfft); // N doubles = 2 * N/2 entries
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mask598.resize(nfft / 4); // N/4 floats
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fft::build_buf548(buf548.data(), nfft);
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fft::build_mask598(mask598.data(), nfft);
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tables_built = true;
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}
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// Step 1: design = ln(mask) and negate (already in real domain)
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// Input is real mask [nbin], convert to real array for RFFT
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std::vector<double> design(nfft, 0.0);
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for (size_t i = 0; i <= half; i++) {
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float m = mask[i];
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if (m > 1e-12f) {
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float ln_m = soothe2::ln_plugin_f32(m);
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ln_m = -ln_m;
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H[i] = std::complex<double>(static_cast<double>(ln_m), 0.0);
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design[i] = -static_cast<double>(ln_m);
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} else {
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H[i] = std::complex<double>(0.0, 0.0);
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design[i] = 0.0;
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}
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}
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// Zero upper half
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for (size_t i = half + 1; i < nfft; i++) {
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H[i] = std::complex<double>(0.0, 0.0);
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}
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// IFFT to time domain
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fft::execute_inverse(&plan_, H.data());
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// Causal window: keep first half, apply rising Hann (0.5→1.0)
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for (size_t i = 0; i < half; i++) {
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double win = 0.5 * (1.0 - std::cos(2.0 * M_PI * i / nfft));
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H[i] *= win;
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}
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for (size_t i = half; i < nfft; i++) {
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H[i] = std::complex<double>(0.0, 0.0);
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}
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// FFT back to freq domain
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fft::execute(&plan_, H.data());
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// Apply WIN_freq window
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if (!win_freq_.empty() && win_freq_.size() > half) {
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// Step 2: opA = inv-RFFT (th2180): design (real) → time domain
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// But wait: inv-RFFT takes N/2+1 complex → N real
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// We need to pack design as complex first (im=0)
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std::vector<std::complex<double>> H(half + 1);
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for (size_t i = 0; i <= half; i++) {
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H[i] *= static_cast<double>(win_freq_[i]);
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}
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H[i] = std::complex<double>(design[i], 0.0);
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}
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// Zero upper half again
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std::vector<double> time_domain(nfft);
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fft::execute_real_inverse_exact(&plan_, H.data(), time_domain.data(), buf548.data(), mask598.data());
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// Step 3: fold - from BLOCKMAP: "FIR[n]=0 (n=0x540534=4096!)"
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// This zeroes FIR[4096] which is out of bounds for size 4096 array - likely means FIR[nfft]=0 (past end)
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// Then: "52d920(&FIR[1], xmm13, n/2−1) деление" - DIVIDE FIR[1..2047]
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// "52db50(&FIR[2049], xmm9, n/2−1)" - multiply/zero FIR[2049..4095]
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// xmm13 and xmm9 values unknown, but 52d920 is DIVIDE so likely scale by 0.5
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// 52db50 with xmm9=0 would zero the upper half
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for (size_t i = 1; i <= half; i++) {
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time_domain[i] *= 0.5; // DIVIDE by 2 (xmm13 = 0.5?)
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}
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for (size_t i = half + 1; i < nfft; i++) {
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H[i] = std::complex<double>(0.0, 0.0);
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time_domain[i] = 0.0; // xmm9 = 0 zeros upper half
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}
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for (size_t i = half + 1; i < nfft; i++) {
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time_domain[i] = 0.0;
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}
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// Normalize: FIR[0]=1, FIR[1]=0
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double scale = 1.0;
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if (std::abs(H[0].real()) > 1e-12) {
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scale = 1.0 / H[0].real();
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// Step 4: opB = fwd-RFFT (th1a90): time_domain (real) → complex
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std::vector<std::complex<double>> freq_domain(half + 1);
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fft::execute_real_forward_exact(&plan_, time_domain.data(), freq_domain.data(), buf548.data(), mask598.data());
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// Step 5: EXP: complex polynomial exp with q≈0.80 scaling
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// From BLOCKMAP: "EXP#2 (1409e0) on [678i]; += scalar; exp-var 140a40 финал"
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// "140b30(=1803831c0)" is the bigkernel for complex EXP
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// We'll implement a complex exp with q scaling
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double q_scale = 0.80;
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for (size_t i = 0; i <= half; i++) {
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double re = freq_domain[i].real();
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double im = freq_domain[i].imag();
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double mag = std::sqrt(re*re + im*im);
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if (mag > 1e-12) {
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double angle = std::atan2(im, re);
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double exp_mag = std::exp(q_scale * mag);
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freq_domain[i] = std::complex<double>(exp_mag * std::cos(angle), exp_mag * std::sin(angle));
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} else {
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freq_domain[i] = std::complex<double>(1.0, 0.0);
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}
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for (size_t i = 0; i < nfft; i++) {
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fir[i] = H[i] * scale;
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}
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// Step 6: opC = inv-RFFT (th2180): freq_domain → time domain
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std::vector<double> time_domain2(nfft);
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fft::execute_real_inverse_exact(&plan_, freq_domain.data(), time_domain2.data(), buf548.data(), mask598.data());
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// Step 7: zero Nyquist (FIR[n]=0 where n=4096, out of bounds)
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// Then: 52d990(FIR, WIN_freq+n/2, n/2) УМНОЖЕНИЕ на падающую половину Hann
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// This multiplies FIR[2048..4095] by falling Hann window
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// WIN_freq is periodic Hann (rising 0→1), WIN_freq+n/2 is the SECOND half (falling 1→0)
|
||||
// w[1024]=0.5, w[2048]=1.0 means:
|
||||
// - For i=2048 (offset 0): window = WIN_freq[2048+0] = WIN_freq[2048] = 1.0
|
||||
// - For i=3072 (offset 1024): window = WIN_freq[2048+1024] = WIN_freq[3072] = 0.5
|
||||
// - For i=4095 (offset 2047): window = WIN_freq[2048+2047] = WIN_freq[4095] = 0.0
|
||||
for (size_t i = half; i < nfft; i++) {
|
||||
size_t win_idx = half + (i - half);
|
||||
if (win_idx < win_freq_.size()) {
|
||||
time_domain2[i] *= static_cast<double>(win_freq_[win_idx]);
|
||||
} else {
|
||||
// Falling Hann: 0.5 * (1.0 + cos(2*pi*i/N))
|
||||
double win = 0.5 * (1.0 + std::cos(2.0 * M_PI * (i - half) / nfft));
|
||||
time_domain2[i] *= win;
|
||||
}
|
||||
}
|
||||
|
||||
// Step 9: opD = fwd-RFFT (th1a90): windowed time → final FIR
|
||||
fft::execute_real_forward_exact(&plan_, time_domain2.data(), fir, buf548.data(), mask598.data());
|
||||
|
||||
// Step 10: normalize: FIR[0]=1.0, FIR[1]=0.0
|
||||
fir[0] = std::complex<double>(1.0, 0.0);
|
||||
if (half >= 1) {
|
||||
if (half > 1) {
|
||||
fir[1] = std::complex<double>(0.0, 0.0);
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user