Merge branch 'worktree-agent-a9867cbf'

encode/mp3.go

@@ -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

@@ -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
+	layers       map[classify.TrafficClass]*Layer
-	tau    float64
+	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),
+		layers:       make(map[classify.TrafficClass]*Layer, len(cfgs)),
-		tau:    tau,
+		tau:          tau,
+		gainPerLayer: 1.0 / float64(len(cfgs)),
 	}
-	for _, class := range classify.AllClasses() {
+	for class, cfg := range cfgs {
-		cfg := ClassFreqConfigs[class]
 		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() {
+		for _, layer := range b.layers {
-			layer := b.layers[class]
 			sample := layer.AdvanceSample()
 			gainL, gainR := PanGains(layer.Config.Pan)
-			sumL += sample * GainPerLayer * gainL
+			sumL += sample * b.gainPerLayer * gainL
-			sumR += sample * GainPerLayer * gainR
+			sumR += sample * b.gainPerLayer * gainR
 		}
 		frames[i] = [2]float64{sumL, sumR}
 	}

synth/bank_test.go

@@ -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

@@ -59,7 +59,8 @@ func TestClassFreqConfigsComplete(t *testing.T) {
 }
 
 func TestNumLayersMatchesAllClasses(t *testing.T) {
-	if synth.NumLayers != len(classify.AllClasses()) {
+	if len(synth.ClassFreqConfigs) != len(classify.AllClasses()) {
-		t.Errorf("NumLayers=%d but AllClasses() has %d entries", synth.NumLayers, len(classify.AllClasses()))
+		t.Errorf("ClassFreqConfigs has %d entries but AllClasses() has %d entries",
+			len(synth.ClassFreqConfigs), len(classify.AllClasses()))
 	}
 }