gurixandClaude Opus 4.6
6b2db48339
Replace static EMA-smoothed drones with an evolving ambient soundscape: - ADSR envelope system with sustained (2s attack, 4s release) and bursty (30ms attack, no sustain) modes per protocol group - LFO pitch wobble and amplitude tremolo with incommensurable rates per group (Eno technique) so modulation patterns never repeat - C major pentatonic frequency tuning (just intonation) — any combination of active protocols sounds consonant - tanh soft limiter on master output prevents clipping - Sync all documentation: README, PROJECT.md, ARCHITECTURE.md, v1.2 requirements traceability Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
74 lines
2.3 KiB
Go
74 lines
2.3 KiB
Go
package synth
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import (
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"math"
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"github.com/netsynth/netsynth/classify"
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)
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// OscillatorBank holds synthesis layers, one per TrafficClass in the injected config map.
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// It consumes WindowSnapshot data and renders stereo PCM frames.
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type OscillatorBank struct {
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layers map[classify.TrafficClass]*Layer
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tau float64
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gainPerLayer float64
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}
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// maxTremoloDepth is the highest tremolo depth across all groups.
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// Used to compute headroom so tremolo doesn't cause clipping.
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const maxTremoloDepth = 0.20
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// NewBank creates an OscillatorBank with one Layer per entry in cfgs.
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// tau is the EMA time constant in seconds (use 1.0 for D-07's "1-2 second" feel).
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// gainPerLayer accounts for tremolo headroom: 1 / (N * (1 + maxTremoloDepth)).
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func NewBank(tau float64, cfgs map[classify.TrafficClass]FreqConfig) *OscillatorBank {
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b := &OscillatorBank{
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layers: make(map[classify.TrafficClass]*Layer, len(cfgs)),
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tau: tau,
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gainPerLayer: 1.0 / (float64(len(cfgs)) * (1.0 + maxTremoloDepth)),
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}
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for class, cfg := range cfgs {
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b.layers[class] = NewLayer(cfg, SampleRate, tau)
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}
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return b
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}
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// RenderWindow updates amplitude targets from snap, then renders SamplesPerWindow
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// stereo frames. Each frame is [2]float64{left, right} with values in [-1, 1].
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// Each layer gets gain with tremolo headroom. A soft limiter prevents any residual clipping.
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func (b *OscillatorBank) RenderWindow(snap classify.WindowSnapshot) [][2]float64 {
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// Find max count for normalization
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var maxCount int64
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for _, count := range snap.Counts {
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if count > maxCount {
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maxCount = count
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}
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}
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// Update target amplitudes for all layers
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for class, layer := range b.layers {
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count := snap.Counts[class]
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layer.UpdateTarget(count, maxCount)
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}
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// Render frames
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frames := make([][2]float64, SamplesPerWindow)
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for i := range frames {
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var sumL, sumR float64
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for _, layer := range b.layers {
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sample := layer.AdvanceSample()
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gainL, gainR := PanGains(layer.Config.Pan)
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sumL += sample * b.gainPerLayer * gainL
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sumR += sample * b.gainPerLayer * gainR
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}
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frames[i] = [2]float64{softLimit(sumL), softLimit(sumR)}
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}
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return frames
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}
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// softLimit applies a tanh-based soft limiter to prevent clipping.
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// Values within [-0.9, 0.9] pass nearly linearly; beyond that, they compress smoothly.
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func softLimit(x float64) float64 {
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return math.Tanh(x)
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}
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