package synth

import "github.com/netsynth/netsynth/classify"

// OscillatorBank holds 11 synthesis layers, one per TrafficClass.
// It consumes WindowSnapshot data and renders stereo PCM frames.
type OscillatorBank struct {
	layers map[classify.TrafficClass]*Layer
	tau    float64
}

// NewBank creates an OscillatorBank with one Layer per TrafficClass.
// tau is the EMA time constant in seconds (use 1.0 for D-07's "1-2 second" feel).
func NewBank(tau float64) *OscillatorBank {
	b := &OscillatorBank{
		layers: make(map[classify.TrafficClass]*Layer, NumLayers),
		tau:    tau,
	}
	for _, class := range classify.AllClasses() {
		cfg := ClassFreqConfigs[class]
		b.layers[class] = NewLayer(cfg, SampleRate, tau)
	}
	return b
}

// 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).
func (b *OscillatorBank) RenderWindow(snap classify.WindowSnapshot) [][2]float64 {
	// Find max count for normalization
	var maxCount int64
	for _, count := range snap.Counts {
		if count > maxCount {
			maxCount = count
		}
	}

	// Update target amplitudes for all layers
	for _, class := range classify.AllClasses() {
		count := snap.Counts[class]
		b.layers[class].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]
			sample := layer.AdvanceSample()
			gainL, gainR := PanGains(layer.Config.Pan)
			sumL += sample * GainPerLayer * gainL
			sumR += sample * GainPerLayer * gainR
		}
		frames[i] = [2]float64{sumL, sumR}
	}
	return frames
}