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Merge branch 'worktree-agent-a9867cbf'

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gurix
2026-03-26 17:40:03 +01:00
parent 8e357cf432 b2b5ab679b
commit d436ef154d
4 changed files with 69 additions and 28 deletions
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encode/mp3.go
+1 -1
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@@ -54,7 +54,7 @@ func RunSynthesis(snapshots []classify.WindowSnapshot, outputPath string) error
}
// Render all windows to stereo frames
bank := synth.NewBank(1.0) // tau=1.0s per D-07
bank := synth.NewBank(1.0, synth.ClassFreqConfigs) // tau=1.0s per D-07
var allFrames [][2]float64
for _, snap := range snapshots {
frames := bank.RenderWindow(snap)
synth/bank.go
+18 -16
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@@ -2,22 +2,25 @@ package synth
import "github.com/netsynth/netsynth/classify"
// OscillatorBank holds 11 synthesis layers, one per TrafficClass.
// OscillatorBank holds synthesis layers, one per TrafficClass in the injected config map.
// It consumes WindowSnapshot data and renders stereo PCM frames.
type OscillatorBank struct {
layers map[classify.TrafficClass]*Layer
tau float64
layers map[classify.TrafficClass]*Layer
tau float64
gainPerLayer float64
}
// NewBank creates an OscillatorBank with one Layer per TrafficClass.
// NewBank creates an OscillatorBank with one Layer per entry in cfgs.
// tau is the EMA time constant in seconds (use 1.0 for D-07's "1-2 second" feel).
func NewBank(tau float64) *OscillatorBank {
// gainPerLayer is computed dynamically as 1/len(cfgs) so that all layers at max
// amplitude sum to exactly 1.0 (no clipping), regardless of how many classes are active.
func NewBank(tau float64, cfgs map[classify.TrafficClass]FreqConfig) *OscillatorBank {
b := &OscillatorBank{
layers: make(map[classify.TrafficClass]*Layer, NumLayers),
tau: tau,
layers: make(map[classify.TrafficClass]*Layer, len(cfgs)),
tau: tau,
gainPerLayer: 1.0 / float64(len(cfgs)),
}
for _, class := range classify.AllClasses() {
cfg := ClassFreqConfigs[class]
for class, cfg := range cfgs {
b.layers[class] = NewLayer(cfg, SampleRate, tau)
}
return b
@@ -25,7 +28,7 @@ func NewBank(tau float64) *OscillatorBank {
// RenderWindow updates amplitude targets from snap, then renders SamplesPerWindow
// stereo frames. Each frame is [2]float64{left, right} with values in [-1, 1].
// Per D-10: each layer gets GainPerLayer (1/11) so 11 max-amplitude layers sum to 1.0 (no clipping).
// Each layer gets 1/N of the total gain where N is the number of layers.
func (b *OscillatorBank) RenderWindow(snap classify.WindowSnapshot) [][2]float64 {
// Find max count for normalization
var maxCount int64
@@ -36,21 +39,20 @@ func (b *OscillatorBank) RenderWindow(snap classify.WindowSnapshot) [][2]float64
}
// Update target amplitudes for all layers
for _, class := range classify.AllClasses() {
for class, layer := range b.layers {
count := snap.Counts[class]
b.layers[class].UpdateTarget(count, maxCount)
layer.UpdateTarget(count, maxCount)
}
// Render frames
frames := make([][2]float64, SamplesPerWindow)
for i := range frames {
var sumL, sumR float64
for _, class := range classify.AllClasses() {
layer := b.layers[class]
for _, layer := range b.layers {
sample := layer.AdvanceSample()
gainL, gainR := PanGains(layer.Config.Pan)
sumL += sample * GainPerLayer * gainL
sumR += sample * GainPerLayer * gainR
sumL += sample * b.gainPerLayer * gainL
sumR += sample * b.gainPerLayer * gainR
}
frames[i] = [2]float64{sumL, sumR}
}
synth/bank_test.go
+47 -9
View File
@@ -8,7 +8,7 @@ import (
)
func TestNewBankHas14Layers(t *testing.T) {
b := NewBank(1.0)
b := NewBank(1.0, ClassFreqConfigs)
if len(b.layers) != 14 {
t.Errorf("NewBank() has %d layers, want 14", len(b.layers))
}
@@ -21,7 +21,7 @@ func TestNewBankHas14Layers(t *testing.T) {
}
func TestRenderWindowOutputLength(t *testing.T) {
b := NewBank(1.0)
b := NewBank(1.0, ClassFreqConfigs)
snap := classify.WindowSnapshot{
Counts: make(map[classify.TrafficClass]int64),
TotalPackets: 0,
@@ -34,7 +34,7 @@ func TestRenderWindowOutputLength(t *testing.T) {
}
func TestRenderWindowSilentWhenNoTraffic(t *testing.T) {
b := NewBank(1.0)
b := NewBank(1.0, ClassFreqConfigs)
// Empty counts — no class ever seen — all layers should stay at zero amplitude
snap := classify.WindowSnapshot{
Counts: make(map[classify.TrafficClass]int64),
@@ -51,7 +51,7 @@ func TestRenderWindowSilentWhenNoTraffic(t *testing.T) {
}
func TestRenderWindowNonZeroWithTraffic(t *testing.T) {
b := NewBank(1.0)
b := NewBank(1.0, ClassFreqConfigs)
counts := make(map[classify.TrafficClass]int64)
counts[classify.ClassICMP] = 100
snap := classify.WindowSnapshot{
@@ -74,15 +74,15 @@ func TestRenderWindowNonZeroWithTraffic(t *testing.T) {
}
func TestMixerNoClip(t *testing.T) {
b := NewBank(0.01) // fast EMA to quickly ramp up to near-max amplitude
b := NewBank(0.01, ClassFreqConfigs) // fast EMA to quickly ramp up to near-max amplitude
counts := make(map[classify.TrafficClass]int64)
// All 14 classes at max count — worst-case mixing scenario
for _, class := range classify.AllClasses() {
for class := range ClassFreqConfigs {
counts[class] = 1000
}
snap := classify.WindowSnapshot{
Counts: counts,
TotalPackets: 14000,
TotalPackets: int64(len(ClassFreqConfigs)) * 1000,
WindowIndex: 0,
}
// Render multiple windows to let EMA converge
@@ -102,7 +102,7 @@ func TestMixerNoClip(t *testing.T) {
}
func TestStereoPan(t *testing.T) {
b := NewBank(0.01) // fast EMA
b := NewBank(0.01, ClassFreqConfigs) // fast EMA
counts := make(map[classify.TrafficClass]int64)
// ClassDHCP has pan=-0.75 (wide-left in config.go)
counts[classify.ClassDHCP] = 1000
@@ -130,7 +130,7 @@ func TestStereoPan(t *testing.T) {
}
func TestMultipleWindowsEMAConvergence(t *testing.T) {
b := NewBank(1.0)
b := NewBank(1.0, ClassFreqConfigs)
counts := make(map[classify.TrafficClass]int64)
counts[classify.ClassICMP] = 100
snap := classify.WindowSnapshot{
@@ -150,6 +150,44 @@ func TestMultipleWindowsEMAConvergence(t *testing.T) {
}
}
func TestNewBankDynamicGain(t *testing.T) {
// Create a config map with only 3 classes
cfgs := map[classify.TrafficClass]FreqConfig{
classify.ClassICMP: ClassFreqConfigs[classify.ClassICMP],
classify.ClassDNS: ClassFreqConfigs[classify.ClassDNS],
classify.ClassHTTPS: ClassFreqConfigs[classify.ClassHTTPS],
}
b := NewBank(0.01, cfgs)
if len(b.layers) != 3 {
t.Errorf("NewBank with 3 configs has %d layers, want 3", len(b.layers))
}
// Verify gainPerLayer is 1/3
expected := 1.0 / 3.0
if b.gainPerLayer != expected {
t.Errorf("gainPerLayer = %v, want %v", b.gainPerLayer, expected)
}
}
func TestNewBankCustomConfigNoClip(t *testing.T) {
cfgs := map[classify.TrafficClass]FreqConfig{
classify.ClassICMP: ClassFreqConfigs[classify.ClassICMP],
classify.ClassDNS: ClassFreqConfigs[classify.ClassDNS],
}
b := NewBank(0.01, cfgs)
counts := map[classify.TrafficClass]int64{
classify.ClassICMP: 1000,
classify.ClassDNS: 1000,
}
snap := classify.WindowSnapshot{Counts: counts, TotalPackets: 2000, WindowIndex: 0}
for i := 0; i < 10; i++ {
for _, frame := range b.RenderWindow(snap) {
if frame[0] > 1.0 || frame[0] < -1.0 || frame[1] > 1.0 || frame[1] < -1.0 {
t.Fatalf("clipped with 2-class config: L=%v R=%v", frame[0], frame[1])
}
}
}
}
// windowRMS computes the root mean square amplitude across all stereo frames.
func windowRMS(frames [][2]float64) float64 {
var sum float64
synth/config_test.go
+3 -2
View File
@@ -59,7 +59,8 @@ func TestClassFreqConfigsComplete(t *testing.T) {
}
func TestNumLayersMatchesAllClasses(t *testing.T) {
if synth.NumLayers != len(classify.AllClasses()) {
t.Errorf("NumLayers=%d but AllClasses() has %d entries", synth.NumLayers, len(classify.AllClasses()))
if len(synth.ClassFreqConfigs) != len(classify.AllClasses()) {
t.Errorf("ClassFreqConfigs has %d entries but AllClasses() has %d entries",
len(synth.ClassFreqConfigs), len(classify.AllClasses()))
}
}