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906 lines
31 KiB
C
906 lines
31 KiB
C
// Created by CuriousTorvald and Claude on 2025-10-24.
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// TAD32 (Terrarum Advanced Audio - PCM32f version) Encoder Library
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// Alternative version: PCM32f throughout encoding, PCM8 conversion only at decoder
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// This file contains only the encoding functions for comparison testing
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#include <stdio.h>
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#include <stdlib.h>
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#include <stdint.h>
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#include <string.h>
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#include <math.h>
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#include <zstd.h>
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#include "encoder_tad.h"
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// Undefine the macro version from header and define as array
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#undef TAD32_COEFF_SCALARS
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// Coefficient scalars for each subband (CDF 9/7 with 9 decomposition levels)
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// Index 0 = LL band, Index 1-9 = H bands (L9 to L1)
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static const float TAD32_COEFF_SCALARS[] = {64.0f, 45.255f, 32.0f, 22.627f, 16.0f, 11.314f, 8.0f, 5.657f, 4.0f, 2.828f};
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// Base quantiser weight table (10 subbands: LL + 9 H bands)
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// Linearly spaced from 1.0 (LL) to 2.0 (H9)
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// These weights are multiplied by quantiser_scale during quantization
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static const float BASE_QUANTISER_WEIGHTS[] = {
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1.0f, // LL (L9) - finest preservation
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1.111f, // H (L9)
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1.222f, // H (L8)
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1.333f, // H (L7)
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1.444f, // H (L6)
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1.556f, // H (L5)
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1.667f, // H (L4)
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1.778f, // H (L3)
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1.889f, // H (L2)
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2.0f // H (L1) - coarsest quantization
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};
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// Forward declarations for internal functions
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static void dwt_dd4_forward_1d(float *data, int length);
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static void dwt_dd4_forward_multilevel(float *data, int length, int levels);
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static void quantize_dwt_coefficients(const float *coeffs, int8_t *quantized, size_t count, int apply_deadzone, int chunk_size, int dwt_levels, int quant_bits, int *current_subband_index, float quantiser_scale);
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static size_t encode_twobitmap(const int8_t *values, size_t count, uint8_t *output);
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static inline float FCLAMP(float x, float min, float max) {
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return x < min ? min : (x > max ? max : x);
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}
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// Calculate DWT levels from chunk size
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static int calculate_dwt_levels(int chunk_size) {
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/*if (chunk_size < TAD32_MIN_CHUNK_SIZE) {
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fprintf(stderr, "Error: Chunk size %d is below minimum %d\n", chunk_size, TAD32_MIN_CHUNK_SIZE);
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return -1;
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}
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int levels = 0;
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int size = chunk_size;
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while (size > 1) {
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size >>= 1;
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levels++;
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}
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// For non-power-of-2, we need to add 1 to levels
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int pow2 = 1 << levels;
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if (pow2 < chunk_size) {
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levels++;
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}
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return levels - 2;*/ // Maximum decomposition
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return 9;
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}
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//=============================================================================
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// DD-4 DWT Implementation
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//=============================================================================
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// Four-point interpolating Deslauriers-Dubuc (DD-4) wavelet forward 1D transform
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static void dwt_dd4_forward_1d(float *data, int length) {
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if (length < 2) return;
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float *temp = malloc(length * sizeof(float));
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int half = (length + 1) / 2;
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// Split into even/odd samples
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for (int i = 0; i < half; i++) {
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temp[i] = data[2 * i]; // Even (low)
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}
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for (int i = 0; i < length / 2; i++) {
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temp[half + i] = data[2 * i + 1]; // Odd (high)
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}
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// DD-4 forward prediction step with four-point kernel
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for (int i = 0; i < length / 2; i++) {
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float s_m1, s_0, s_1, s_2;
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if (i > 0) s_m1 = temp[i - 1];
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else s_m1 = temp[0]; // Mirror boundary
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s_0 = temp[i];
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if (i + 1 < half) s_1 = temp[i + 1];
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else s_1 = temp[half - 1];
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if (i + 2 < half) s_2 = temp[i + 2];
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else if (half > 1) s_2 = temp[half - 2];
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else s_2 = temp[half - 1];
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float prediction = (-1.0f/16.0f) * s_m1 + (9.0f/16.0f) * s_0 +
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(9.0f/16.0f) * s_1 + (-1.0f/16.0f) * s_2;
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temp[half + i] -= prediction;
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}
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// DD-4 update step
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for (int i = 0; i < half; i++) {
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float d_curr = (i < length / 2) ? temp[half + i] : 0.0f;
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float d_prev = (i > 0 && i - 1 < length / 2) ? temp[half + i - 1] : 0.0f;
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temp[i] += 0.25f * (d_prev + d_curr);
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}
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memcpy(data, temp, length * sizeof(float));
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free(temp);
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}
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// 1D DWT using lifting scheme for 9/7 irreversible filter
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static void dwt_97_forward_1d(float *data, int length) {
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if (length < 2) return;
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float *temp = malloc(length * sizeof(float));
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int half = (length + 1) / 2; // Handle odd lengths properly
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// Split into even/odd samples
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for (int i = 0; i < half; i++) {
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temp[i] = data[2 * i]; // Even (low)
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}
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for (int i = 0; i < length / 2; i++) {
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temp[half + i] = data[2 * i + 1]; // Odd (high)
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}
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// JPEG2000 9/7 forward lifting steps (corrected to match decoder)
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const float alpha = -1.586134342f;
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const float beta = -0.052980118f;
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const float gamma = 0.882911076f;
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const float delta = 0.443506852f;
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const float K = 1.230174105f;
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// Step 1: Predict α - d[i] += α * (s[i] + s[i+1])
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for (int i = 0; i < length / 2; i++) {
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if (half + i < length) {
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float s_curr = temp[i];
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float s_next = (i + 1 < half) ? temp[i + 1] : s_curr;
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temp[half + i] += alpha * (s_curr + s_next);
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}
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}
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// Step 2: Update β - s[i] += β * (d[i-1] + d[i])
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for (int i = 0; i < half; i++) {
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float d_curr = (half + i < length) ? temp[half + i] : 0.0f;
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float d_prev = (i > 0 && half + i - 1 < length) ? temp[half + i - 1] : d_curr;
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temp[i] += beta * (d_prev + d_curr);
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}
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// Step 3: Predict γ - d[i] += γ * (s[i] + s[i+1])
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for (int i = 0; i < length / 2; i++) {
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if (half + i < length) {
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float s_curr = temp[i];
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float s_next = (i + 1 < half) ? temp[i + 1] : s_curr;
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temp[half + i] += gamma * (s_curr + s_next);
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}
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}
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// Step 4: Update δ - s[i] += δ * (d[i-1] + d[i])
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for (int i = 0; i < half; i++) {
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float d_curr = (half + i < length) ? temp[half + i] : 0.0f;
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float d_prev = (i > 0 && half + i - 1 < length) ? temp[half + i - 1] : d_curr;
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temp[i] += delta * (d_prev + d_curr);
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}
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// Step 5: Scaling - s[i] *= K, d[i] /= K
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for (int i = 0; i < half; i++) {
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temp[i] *= K; // Low-pass coefficients
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}
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for (int i = 0; i < length / 2; i++) {
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if (half + i < length) {
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temp[half + i] /= K; // High-pass coefficients
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}
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}
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memcpy(data, temp, length * sizeof(float));
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free(temp);
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}
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// Apply multi-level DWT (using DD-4 wavelet)
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static void dwt_dd4_forward_multilevel(float *data, int length, int levels) {
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int current_length = length;
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for (int level = 0; level < levels; level++) {
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// dwt_dd4_forward_1d(data, current_length);
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dwt_97_forward_1d(data, current_length);
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current_length = (current_length + 1) / 2;
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}
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}
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//=============================================================================
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// M/S Stereo Decorrelation (PCM32f version)
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//=============================================================================
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static void ms_decorrelate(const float *left, const float *right, float *mid, float *side, size_t count) {
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for (size_t i = 0; i < count; i++) {
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// Mid = (L + R) / 2, Side = (L - R) / 2
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float l = left[i];
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float r = right[i];
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mid[i] = (l + r) / 2.0f;
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side[i] = (l - r) / 2.0f;
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}
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}
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static float signum(float x) {
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if (x > 0.0f) return 1.0f;
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if (x < 0.0f) return -1.0f;
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return 0.0f;
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}
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static void compress_gamma(float *left, float *right, size_t count) {
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for (size_t i = 0; i < count; i++) {
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// encode(x) = sign(x) * |x|^γ where γ=0.5
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float x = left[i];
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left[i] = signum(x) * sqrtf(fabsf(x));
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float y = right[i];
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right[i] = signum(y) * sqrtf(fabsf(y));
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}
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}
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static void compress_mu_law(float *left, float *right, size_t count) {
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static float MU = 255.0f;
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for (size_t i = 0; i < count; i++) {
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// encode(x) = sign(x) * |x|^γ where γ=0.5
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float x = left[i];
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left[i] = signum(x) * logf(1.0f + MU * fabsf(x)) / logf(1.0f + MU);
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float y = right[i];
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right[i] = signum(y) * logf(1.0f + MU * fabsf(y)) / logf(1.0f + MU);
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}
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}
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//=============================================================================
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// Quantization with Frequency-Dependent Weighting
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//=============================================================================
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#define LAMBDA_FIXED 6.0f
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// Lambda-based companding encoder (based on Laplacian distribution CDF)
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// val must be normalised to [-1,1]
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// Returns quantized index in range [-127, +127]
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static int8_t lambda_companding(float val, int max_index) {
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// Handle zero
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if (fabsf(val) < 1e-9f) {
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return 0;
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}
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int sign = (val < 0) ? -1 : 1;
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float abs_val = fabsf(val);
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// Clamp to [0, 1]
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if (abs_val > 1.0f) abs_val = 1.0f;
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// Laplacian CDF for x >= 0: F(x) = 1 - 0.5 * exp(-λ*x)
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// Map to [0.5, 1.0] range (half of CDF for positive values)
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float cdf = 1.0f - 0.5f * expf(-LAMBDA_FIXED * abs_val);
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// Map CDF from [0.5, 1.0] to [0, 1] for positive half
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float normalized_cdf = (cdf - 0.5f) * 2.0f;
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// Quantize to index
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int index = (int)roundf(normalized_cdf * max_index);
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// Clamp index to valid range [0, max_index]
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if (index < 0) index = 0;
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if (index > max_index) index = max_index;
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return (int8_t)(sign * index);
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}
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static void quantize_dwt_coefficients(const float *coeffs, int8_t *quantized, size_t count, int apply_deadzone, int chunk_size, int dwt_levels, int max_index, int *current_subband_index, float quantiser_scale) {
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int first_band_size = chunk_size >> dwt_levels;
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int *sideband_starts = malloc((dwt_levels + 2) * sizeof(int));
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sideband_starts[0] = 0;
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sideband_starts[1] = first_band_size;
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for (int i = 2; i <= dwt_levels + 1; i++) {
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sideband_starts[i] = sideband_starts[i-1] + (first_band_size << (i-2));
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}
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for (size_t i = 0; i < count; i++) {
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int sideband = dwt_levels;
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for (int s = 0; s <= dwt_levels; s++) {
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if (i < (size_t)sideband_starts[s + 1]) {
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sideband = s;
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break;
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}
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}
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// Store subband index (LL=0, H1=1, H2=2, ..., H9=9 for dwt_levels=9)
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if (current_subband_index != NULL) {
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current_subband_index[i] = sideband;
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}
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// Apply base weight and quantiser scaling
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float weight = BASE_QUANTISER_WEIGHTS[sideband] * quantiser_scale;
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float val = (coeffs[i] / (TAD32_COEFF_SCALARS[sideband] * weight)); // val is normalised to [-1,1]
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int8_t quant_val = lambda_companding(val, max_index);
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quantized[i] = quant_val;
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}
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free(sideband_starts);
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}
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//=============================================================================
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// Twobit-map Significance Map Encoding
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//=============================================================================
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// Twobit-map encoding: 2 bits per coefficient for common values
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// 00 = 0
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// 01 = +1
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// 10 = -1
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// 11 = other value (followed by int8_t in separate array)
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static size_t encode_twobitmap(const int8_t *values, size_t count, uint8_t *output) {
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// Calculate size needed for twobit map
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size_t map_bytes = (count * 2 + 7) / 8; // 2 bits per coefficient
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// First pass: create significance map and count "other" values
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uint8_t *map = output;
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memset(map, 0, map_bytes);
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size_t other_count = 0;
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for (size_t i = 0; i < count; i++) {
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int8_t val = values[i];
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uint8_t code;
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if (val == 0) {
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code = 0; // 00
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} else if (val == 1) {
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code = 1; // 01
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} else if (val == -1) {
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code = 2; // 10
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} else {
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code = 3; // 11
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other_count++;
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}
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// Write 2-bit code into map
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size_t bit_offset = i * 2;
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size_t byte_idx = bit_offset / 8;
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size_t bit_in_byte = bit_offset % 8;
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map[byte_idx] |= (code << bit_in_byte);
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}
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// Second pass: write "other" values
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int8_t *other_values = (int8_t*)(output + map_bytes);
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size_t other_idx = 0;
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for (size_t i = 0; i < count; i++) {
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int8_t val = values[i];
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if (val != 0 && val != 1 && val != -1) {
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other_values[other_idx++] = val;
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}
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}
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return map_bytes + other_count;
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}
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//=============================================================================
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// Coefficient Statistics
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//=============================================================================
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static int compare_float(const void *a, const void *b) {
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float fa = *(const float*)a;
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float fb = *(const float*)b;
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if (fa < fb) return -1;
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if (fa > fb) return 1;
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return 0;
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}
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typedef struct {
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float min;
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float q1;
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float median;
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float q3;
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float max;
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float lambda; // Laplacian distribution parameter (1/b, where b is scale)
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} CoeffStats;
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typedef struct {
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float *data;
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size_t count;
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size_t capacity;
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} CoeffAccumulator;
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typedef struct {
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int8_t *data;
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size_t count;
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size_t capacity;
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} QuantAccumulator;
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// Global accumulators for statistics
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static CoeffAccumulator *mid_accumulators = NULL;
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static CoeffAccumulator *side_accumulators = NULL;
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static QuantAccumulator *mid_quant_accumulators = NULL;
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static QuantAccumulator *side_quant_accumulators = NULL;
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static int num_subbands = 0;
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static int stats_initialized = 0;
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static int stats_dwt_levels = 0;
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static void init_statistics(int dwt_levels) {
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if (stats_initialized) return;
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num_subbands = dwt_levels + 1;
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stats_dwt_levels = dwt_levels;
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mid_accumulators = calloc(num_subbands, sizeof(CoeffAccumulator));
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side_accumulators = calloc(num_subbands, sizeof(CoeffAccumulator));
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mid_quant_accumulators = calloc(num_subbands, sizeof(QuantAccumulator));
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side_quant_accumulators = calloc(num_subbands, sizeof(QuantAccumulator));
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for (int i = 0; i < num_subbands; i++) {
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mid_accumulators[i].capacity = 1024;
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mid_accumulators[i].data = malloc(mid_accumulators[i].capacity * sizeof(float));
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mid_accumulators[i].count = 0;
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side_accumulators[i].capacity = 1024;
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side_accumulators[i].data = malloc(side_accumulators[i].capacity * sizeof(float));
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side_accumulators[i].count = 0;
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mid_quant_accumulators[i].capacity = 1024;
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mid_quant_accumulators[i].data = malloc(mid_quant_accumulators[i].capacity * sizeof(int8_t));
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mid_quant_accumulators[i].count = 0;
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side_quant_accumulators[i].capacity = 1024;
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side_quant_accumulators[i].data = malloc(side_quant_accumulators[i].capacity * sizeof(int8_t));
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side_quant_accumulators[i].count = 0;
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}
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stats_initialized = 1;
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}
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static void accumulate_coefficients(const float *coeffs, int dwt_levels, int chunk_size, CoeffAccumulator *accumulators) {
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int first_band_size = chunk_size >> dwt_levels;
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int *sideband_starts = malloc((dwt_levels + 2) * sizeof(int));
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sideband_starts[0] = 0;
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sideband_starts[1] = first_band_size;
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for (int i = 2; i <= dwt_levels + 1; i++) {
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sideband_starts[i] = sideband_starts[i-1] + (first_band_size << (i-2));
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}
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for (int s = 0; s <= dwt_levels; s++) {
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size_t start = sideband_starts[s];
|
||
size_t end = sideband_starts[s + 1];
|
||
size_t band_size = end - start;
|
||
|
||
// Expand capacity if needed
|
||
while (accumulators[s].count + band_size > accumulators[s].capacity) {
|
||
accumulators[s].capacity *= 2;
|
||
accumulators[s].data = realloc(accumulators[s].data,
|
||
accumulators[s].capacity * sizeof(float));
|
||
}
|
||
|
||
// Copy coefficients
|
||
memcpy(accumulators[s].data + accumulators[s].count,
|
||
coeffs + start, band_size * sizeof(float));
|
||
accumulators[s].count += band_size;
|
||
}
|
||
|
||
free(sideband_starts);
|
||
}
|
||
|
||
static void accumulate_quantized(const int8_t *quant, int dwt_levels, int chunk_size, QuantAccumulator *accumulators) {
|
||
int first_band_size = chunk_size >> dwt_levels;
|
||
|
||
int *sideband_starts = malloc((dwt_levels + 2) * sizeof(int));
|
||
sideband_starts[0] = 0;
|
||
sideband_starts[1] = first_band_size;
|
||
for (int i = 2; i <= dwt_levels + 1; i++) {
|
||
sideband_starts[i] = sideband_starts[i-1] + (first_band_size << (i-2));
|
||
}
|
||
|
||
for (int s = 0; s <= dwt_levels; s++) {
|
||
size_t start = sideband_starts[s];
|
||
size_t end = sideband_starts[s + 1];
|
||
size_t band_size = end - start;
|
||
|
||
// Expand capacity if needed
|
||
while (accumulators[s].count + band_size > accumulators[s].capacity) {
|
||
accumulators[s].capacity *= 2;
|
||
accumulators[s].data = realloc(accumulators[s].data,
|
||
accumulators[s].capacity * sizeof(int8_t));
|
||
}
|
||
|
||
// Copy coefficients
|
||
memcpy(accumulators[s].data + accumulators[s].count,
|
||
quant + start, band_size * sizeof(int8_t));
|
||
accumulators[s].count += band_size;
|
||
}
|
||
|
||
free(sideband_starts);
|
||
}
|
||
|
||
static void calculate_coeff_stats(const float *coeffs, size_t count, CoeffStats *stats) {
|
||
if (count == 0) {
|
||
stats->min = stats->q1 = stats->median = stats->q3 = stats->max = 0.0f;
|
||
stats->lambda = 0.0f;
|
||
return;
|
||
}
|
||
|
||
// Copy coefficients for sorting
|
||
float *sorted = malloc(count * sizeof(float));
|
||
memcpy(sorted, coeffs, count * sizeof(float));
|
||
qsort(sorted, count, sizeof(float), compare_float);
|
||
|
||
stats->min = sorted[0];
|
||
stats->max = sorted[count - 1];
|
||
stats->median = sorted[count / 2];
|
||
stats->q1 = sorted[count / 4];
|
||
stats->q3 = sorted[(3 * count) / 4];
|
||
|
||
free(sorted);
|
||
|
||
// Estimate Laplacian distribution parameter λ = 1/b
|
||
// For Laplacian centered at μ=0, MLE gives: b = mean(|x|)
|
||
// Therefore: λ = 1/b = 1/mean(|x|)
|
||
double sum_abs = 0.0;
|
||
for (size_t i = 0; i < count; i++) {
|
||
sum_abs += fabs(coeffs[i]);
|
||
}
|
||
double mean_abs = sum_abs / count;
|
||
stats->lambda = (mean_abs > 1e-9) ? (1.0f / mean_abs) : 0.0f;
|
||
}
|
||
|
||
#define HISTOGRAM_BINS 40
|
||
#define HISTOGRAM_WIDTH 60
|
||
|
||
static void print_histogram(const float *coeffs, size_t count, const char *title) {
|
||
if (count == 0) return;
|
||
|
||
// Find min/max
|
||
float min_val = coeffs[0];
|
||
float max_val = coeffs[0];
|
||
for (size_t i = 1; i < count; i++) {
|
||
if (coeffs[i] < min_val) min_val = coeffs[i];
|
||
if (coeffs[i] > max_val) max_val = coeffs[i];
|
||
}
|
||
|
||
// Handle case where all values are the same
|
||
if (fabsf(max_val - min_val) < 1e-9f) {
|
||
fprintf(stderr, " %s: All values are %.3f\n", title, min_val);
|
||
return;
|
||
}
|
||
|
||
// Create histogram bins
|
||
size_t bins[HISTOGRAM_BINS] = {0};
|
||
float bin_width = (max_val - min_val) / HISTOGRAM_BINS;
|
||
|
||
for (size_t i = 0; i < count; i++) {
|
||
int bin = (int)((coeffs[i] - min_val) / bin_width);
|
||
if (bin >= HISTOGRAM_BINS) bin = HISTOGRAM_BINS - 1;
|
||
if (bin < 0) bin = 0;
|
||
bins[bin]++;
|
||
}
|
||
|
||
// Find max bin count for scaling
|
||
size_t max_bin = 0;
|
||
for (int i = 0; i < HISTOGRAM_BINS; i++) {
|
||
if (bins[i] > max_bin) max_bin = bins[i];
|
||
}
|
||
|
||
// Print histogram
|
||
fprintf(stderr, " %s Histogram (range: %.3f to %.3f):\n", title, min_val, max_val);
|
||
|
||
// Print top 20 bins to keep output manageable
|
||
for (int i = 0; i < HISTOGRAM_BINS; i++) {
|
||
float bin_start = min_val + i * bin_width;
|
||
float bin_end = bin_start + bin_width;
|
||
int bar_width = (int)((bins[i] * HISTOGRAM_WIDTH) / max_bin);
|
||
|
||
// Only print bins with significant content (> 1% of max)
|
||
if (bins[i] > max_bin / 100) {
|
||
fprintf(stderr, " %8.3f-%8.3f [%7zu]: ", bin_start, bin_end, bins[i]);
|
||
for (int j = 0; j < bar_width; j++) {
|
||
fprintf(stderr, "█");
|
||
}
|
||
fprintf(stderr, "\n");
|
||
}
|
||
}
|
||
fprintf(stderr, "\n");
|
||
}
|
||
|
||
typedef struct {
|
||
int8_t value;
|
||
size_t count;
|
||
float percentage;
|
||
} ValueFrequency;
|
||
|
||
static int compare_value_frequency(const void *a, const void *b) {
|
||
const ValueFrequency *va = (const ValueFrequency*)a;
|
||
const ValueFrequency *vb = (const ValueFrequency*)b;
|
||
// Sort by count descending
|
||
if (vb->count > va->count) return 1;
|
||
if (vb->count < va->count) return -1;
|
||
return 0;
|
||
}
|
||
|
||
static void print_top5_quantized_values(const int8_t *quant, size_t count, const char *title) {
|
||
if (count == 0) {
|
||
fprintf(stderr, " %s: No data\n", title);
|
||
return;
|
||
}
|
||
|
||
// For int8_t range is at most 256, so we can use direct indexing
|
||
// Map from [-128, 127] to [0, 255]
|
||
size_t freq[256] = {0};
|
||
|
||
for (size_t i = 0; i < count; i++) {
|
||
int idx = (int)quant[i] + 128;
|
||
freq[idx]++;
|
||
}
|
||
|
||
// Find all unique values with their frequencies
|
||
ValueFrequency values[256];
|
||
int unique_count = 0;
|
||
for (int i = 0; i < 256; i++) {
|
||
if (freq[i] > 0) {
|
||
values[unique_count].value = (int8_t)(i - 128);
|
||
values[unique_count].count = freq[i];
|
||
values[unique_count].percentage = (float)(freq[i] * 100.0) / count;
|
||
unique_count++;
|
||
}
|
||
}
|
||
|
||
// Sort by frequency
|
||
qsort(values, unique_count, sizeof(ValueFrequency), compare_value_frequency);
|
||
|
||
// Print top 10
|
||
fprintf(stderr, " %s Top 100 Values:\n", title);
|
||
int print_count = (unique_count < 100) ? unique_count : 100;
|
||
for (int i = 0; i < print_count; i++) {
|
||
fprintf(stderr, " %6d: %8zu occurrences (%5.2f%%)\n",
|
||
values[i].value, values[i].count, values[i].percentage);
|
||
}
|
||
fprintf(stderr, "\n");
|
||
}
|
||
|
||
void tad32_print_statistics(void) {
|
||
if (!stats_initialized) return;
|
||
|
||
fprintf(stderr, "\n=== TAD Coefficient Statistics (before quantization) ===\n");
|
||
|
||
// Print Mid channel statistics
|
||
fprintf(stderr, "\nMid Channel:\n");
|
||
fprintf(stderr, "%-12s %10s %10s %10s %10s %10s %10s %10s\n",
|
||
"Subband", "Samples", "Min", "Q1", "Median", "Q3", "Max", "Lambda");
|
||
fprintf(stderr, "----------------------------------------------------------------------------------------\n");
|
||
|
||
for (int s = 0; s < num_subbands; s++) {
|
||
CoeffStats stats;
|
||
calculate_coeff_stats(mid_accumulators[s].data, mid_accumulators[s].count, &stats);
|
||
|
||
char band_name[16];
|
||
if (s == 0) {
|
||
snprintf(band_name, sizeof(band_name), "LL (L%d)", stats_dwt_levels);
|
||
} else {
|
||
snprintf(band_name, sizeof(band_name), "H (L%d)", stats_dwt_levels - s + 1);
|
||
}
|
||
|
||
fprintf(stderr, "%-12s %10zu %10.3f %10.3f %10.3f %10.3f %10.3f %10.3f\n",
|
||
band_name, mid_accumulators[s].count,
|
||
stats.min, stats.q1, stats.median, stats.q3, stats.max, stats.lambda);
|
||
}
|
||
|
||
// Print Mid channel histograms
|
||
fprintf(stderr, "\nMid Channel Histograms:\n");
|
||
for (int s = 0; s < num_subbands; s++) {
|
||
char band_name[32];
|
||
if (s == 0) {
|
||
snprintf(band_name, sizeof(band_name), "LL (L%d)", stats_dwt_levels);
|
||
} else {
|
||
snprintf(band_name, sizeof(band_name), "H (L%d)", stats_dwt_levels - s + 1);
|
||
}
|
||
print_histogram(mid_accumulators[s].data, mid_accumulators[s].count, band_name);
|
||
}
|
||
|
||
// Print Side channel statistics
|
||
fprintf(stderr, "\nSide Channel:\n");
|
||
fprintf(stderr, "%-12s %10s %10s %10s %10s %10s %10s %10s\n",
|
||
"Subband", "Samples", "Min", "Q1", "Median", "Q3", "Max", "Lambda");
|
||
fprintf(stderr, "----------------------------------------------------------------------------------------\n");
|
||
|
||
for (int s = 0; s < num_subbands; s++) {
|
||
CoeffStats stats;
|
||
calculate_coeff_stats(side_accumulators[s].data, side_accumulators[s].count, &stats);
|
||
|
||
char band_name[16];
|
||
if (s == 0) {
|
||
snprintf(band_name, sizeof(band_name), "LL (L%d)", stats_dwt_levels);
|
||
} else {
|
||
snprintf(band_name, sizeof(band_name), "H (L%d)", stats_dwt_levels - s + 1);
|
||
}
|
||
|
||
fprintf(stderr, "%-12s %10zu %10.3f %10.3f %10.3f %10.3f %10.3f %10.3f\n",
|
||
band_name, side_accumulators[s].count,
|
||
stats.min, stats.q1, stats.median, stats.q3, stats.max, stats.lambda);
|
||
}
|
||
|
||
// Print Side channel histograms
|
||
fprintf(stderr, "\nSide Channel Histograms:\n");
|
||
for (int s = 0; s < num_subbands; s++) {
|
||
char band_name[32];
|
||
if (s == 0) {
|
||
snprintf(band_name, sizeof(band_name), "LL (L%d)", stats_dwt_levels);
|
||
} else {
|
||
snprintf(band_name, sizeof(band_name), "H (L%d)", stats_dwt_levels - s + 1);
|
||
}
|
||
print_histogram(side_accumulators[s].data, side_accumulators[s].count, band_name);
|
||
}
|
||
|
||
// Print quantized values statistics
|
||
fprintf(stderr, "\n=== TAD Quantized Values Statistics (after quantization) ===\n");
|
||
|
||
// Print Mid channel quantized values
|
||
fprintf(stderr, "\nMid Channel Quantized Values:\n");
|
||
for (int s = 0; s < num_subbands; s++) {
|
||
char band_name[32];
|
||
if (s == 0) {
|
||
snprintf(band_name, sizeof(band_name), "LL (L%d)", stats_dwt_levels);
|
||
} else {
|
||
snprintf(band_name, sizeof(band_name), "H (L%d)", stats_dwt_levels - s + 1);
|
||
}
|
||
print_top5_quantized_values(mid_quant_accumulators[s].data, mid_quant_accumulators[s].count, band_name);
|
||
}
|
||
|
||
// Print Side channel quantized values
|
||
fprintf(stderr, "\nSide Channel Quantized Values:\n");
|
||
for (int s = 0; s < num_subbands; s++) {
|
||
char band_name[32];
|
||
if (s == 0) {
|
||
snprintf(band_name, sizeof(band_name), "LL (L%d)", stats_dwt_levels);
|
||
} else {
|
||
snprintf(band_name, sizeof(band_name), "H (L%d)", stats_dwt_levels - s + 1);
|
||
}
|
||
print_top5_quantized_values(side_quant_accumulators[s].data, side_quant_accumulators[s].count, band_name);
|
||
}
|
||
|
||
fprintf(stderr, "\n");
|
||
}
|
||
|
||
void tad32_free_statistics(void) {
|
||
if (!stats_initialized) return;
|
||
|
||
for (int i = 0; i < num_subbands; i++) {
|
||
free(mid_accumulators[i].data);
|
||
free(side_accumulators[i].data);
|
||
free(mid_quant_accumulators[i].data);
|
||
free(side_quant_accumulators[i].data);
|
||
}
|
||
free(mid_accumulators);
|
||
free(side_accumulators);
|
||
free(mid_quant_accumulators);
|
||
free(side_quant_accumulators);
|
||
|
||
mid_accumulators = NULL;
|
||
side_accumulators = NULL;
|
||
mid_quant_accumulators = NULL;
|
||
side_quant_accumulators = NULL;
|
||
stats_initialized = 0;
|
||
}
|
||
|
||
//=============================================================================
|
||
// Public API: Chunk Encoding
|
||
//=============================================================================
|
||
|
||
size_t tad32_encode_chunk(const float *pcm32_stereo, size_t num_samples,
|
||
int max_index, int use_zstd, int use_twobitmap,
|
||
float quantiser_scale, uint8_t *output) {
|
||
// Calculate DWT levels from chunk size
|
||
int dwt_levels = calculate_dwt_levels(num_samples);
|
||
if (dwt_levels < 0) {
|
||
fprintf(stderr, "Error: Invalid chunk size %zu\n", num_samples);
|
||
return 0;
|
||
}
|
||
|
||
// Allocate working buffers (PCM32f throughout, int32 coefficients)
|
||
float *pcm32_left = malloc(num_samples * sizeof(float));
|
||
float *pcm32_right = malloc(num_samples * sizeof(float));
|
||
float *pcm32_mid = malloc(num_samples * sizeof(float));
|
||
float *pcm32_side = malloc(num_samples * sizeof(float));
|
||
|
||
float *dwt_mid = malloc(num_samples * sizeof(float));
|
||
float *dwt_side = malloc(num_samples * sizeof(float));
|
||
|
||
int8_t *quant_mid = malloc(num_samples * sizeof(int8_t));
|
||
int8_t *quant_side = malloc(num_samples * sizeof(int8_t));
|
||
|
||
// Step 1: Deinterleave stereo
|
||
for (size_t i = 0; i < num_samples; i++) {
|
||
pcm32_left[i] = pcm32_stereo[i * 2];
|
||
pcm32_right[i] = pcm32_stereo[i * 2 + 1];
|
||
}
|
||
|
||
// Step 1.1: Compress dynamic range
|
||
compress_gamma(pcm32_left, pcm32_right, num_samples);
|
||
|
||
// Step 2: M/S decorrelation
|
||
ms_decorrelate(pcm32_left, pcm32_right, pcm32_mid, pcm32_side, num_samples);
|
||
|
||
// Step 3: Convert to float and apply DWT
|
||
for (size_t i = 0; i < num_samples; i++) {
|
||
dwt_mid[i] = pcm32_mid[i];
|
||
dwt_side[i] = pcm32_side[i];
|
||
}
|
||
|
||
dwt_dd4_forward_multilevel(dwt_mid, num_samples, dwt_levels);
|
||
dwt_dd4_forward_multilevel(dwt_side, num_samples, dwt_levels);
|
||
|
||
// Step 3.5: Accumulate coefficient statistics if enabled
|
||
static int stats_enabled = -1;
|
||
if (stats_enabled == -1) {
|
||
stats_enabled = 1;//getenv("TAD_COEFF_STATS") != NULL;
|
||
if (stats_enabled) {
|
||
init_statistics(dwt_levels);
|
||
}
|
||
}
|
||
if (stats_enabled) {
|
||
accumulate_coefficients(dwt_mid, dwt_levels, num_samples, mid_accumulators);
|
||
accumulate_coefficients(dwt_side, dwt_levels, num_samples, side_accumulators);
|
||
}
|
||
|
||
// Step 4: Quantize with frequency-dependent weights and quantiser scaling
|
||
quantize_dwt_coefficients(dwt_mid, quant_mid, num_samples, 1, num_samples, dwt_levels, max_index, NULL, quantiser_scale);
|
||
quantize_dwt_coefficients(dwt_side, quant_side, num_samples, 1, num_samples, dwt_levels, max_index, NULL, quantiser_scale);
|
||
|
||
// Step 4.5: Accumulate quantized coefficient statistics if enabled
|
||
if (stats_enabled) {
|
||
accumulate_quantized(quant_mid, dwt_levels, num_samples, mid_quant_accumulators);
|
||
accumulate_quantized(quant_side, dwt_levels, num_samples, side_quant_accumulators);
|
||
}
|
||
|
||
// Step 5: Encode with twobit-map significance map or raw int8_t storage
|
||
uint8_t *temp_buffer = malloc(num_samples * 4); // Generous buffer
|
||
size_t mid_size, side_size;
|
||
|
||
// Raw int8_t storage
|
||
memcpy(temp_buffer, quant_mid, num_samples);
|
||
mid_size = num_samples;
|
||
memcpy(temp_buffer + mid_size, quant_side, num_samples);
|
||
side_size = num_samples;
|
||
|
||
size_t uncompressed_size = mid_size + side_size;
|
||
|
||
// Step 6: Optional Zstd compression
|
||
uint8_t *write_ptr = output;
|
||
|
||
// Write chunk header
|
||
*((uint16_t*)write_ptr) = (uint16_t)num_samples;
|
||
write_ptr += sizeof(uint16_t);
|
||
|
||
*write_ptr = (uint8_t)max_index;
|
||
write_ptr += sizeof(uint8_t);
|
||
|
||
uint32_t *payload_size_ptr = (uint32_t*)write_ptr;
|
||
write_ptr += sizeof(uint32_t);
|
||
|
||
size_t payload_size;
|
||
|
||
if (use_zstd) {
|
||
size_t zstd_bound = ZSTD_compressBound(uncompressed_size);
|
||
uint8_t *zstd_buffer = malloc(zstd_bound);
|
||
|
||
payload_size = ZSTD_compress(zstd_buffer, zstd_bound, temp_buffer, uncompressed_size, TAD32_ZSTD_LEVEL);
|
||
|
||
if (ZSTD_isError(payload_size)) {
|
||
fprintf(stderr, "Error: Zstd compression failed: %s\n", ZSTD_getErrorName(payload_size));
|
||
free(zstd_buffer);
|
||
free(pcm32_left); free(pcm32_right);
|
||
free(pcm32_mid); free(pcm32_side); free(dwt_mid); free(dwt_side);
|
||
free(quant_mid); free(quant_side); free(temp_buffer);
|
||
return 0;
|
||
}
|
||
|
||
memcpy(write_ptr, zstd_buffer, payload_size);
|
||
free(zstd_buffer);
|
||
} else {
|
||
payload_size = uncompressed_size;
|
||
memcpy(write_ptr, temp_buffer, payload_size);
|
||
}
|
||
|
||
*payload_size_ptr = (uint32_t)payload_size;
|
||
write_ptr += payload_size;
|
||
|
||
// Cleanup
|
||
free(pcm32_left); free(pcm32_right);
|
||
free(pcm32_mid); free(pcm32_side); free(dwt_mid); free(dwt_side);
|
||
free(quant_mid); free(quant_side); free(temp_buffer);
|
||
|
||
return write_ptr - output;
|
||
}
|