fix(streamer): db-scaled spectrum so bars match frontend visibility

streamer/src/fft.ts

@@ -69,14 +69,19 @@ export class SpectrumAnalyzer {
     fftInPlace(re, im);
 
     const alpha = this.opts.smoothing ?? 0.6;
-    const peakRef = this.fftSize / 4;
+    // db scaling — same idea as web audio's getByteFrequencyData.
+    // hann-windowed full-scale sine has peak mag ~ fftSize/2; reference to that.
+    const ref = this.fftSize / 2;
+    const dbMin = -80;
+    const dbMax = -20;
     for (let i = 0; i < this.opts.bars; i++) {
       let mag = 0;
       const s = this.bandStarts[i]!;
       const e = this.bandEnds[i]!;
       for (let k = s; k < e; k++) mag += Math.sqrt(re[k]! * re[k]! + im[k]! * im[k]!);
       mag /= e - s;
-      const norm = Math.min(1, mag / peakRef);
+      const db = 20 * Math.log10(Math.max(mag, 1e-9) / ref);
+      const norm = Math.max(0, Math.min(1, (db - dbMin) / (dbMax - dbMin)));
       this.smooth[i] = alpha * this.smooth[i]! + (1 - alpha) * norm;
     }
   }

streamer/tests/fft.test.ts

@@ -23,13 +23,14 @@ describe("SpectrumAnalyzer", () => {
     });
   });
 
-  it("a 1khz sine puts most energy in low bars (logarithmic binning)", () => {
+  it("a 200hz sine puts most energy in low bars (logarithmic binning)", () => {
     const a = new SpectrumAnalyzer({ bars: 48, sampleRate: 48000 });
-    a.feed(sineFrame(1000));
+    for (let n = 0; n < 4; n++) a.feed(sineFrame(200));
     const bars = a.bars();
     const lowSum = bars.slice(0, 16).reduce((s, v) => s + v, 0);
     const highSum = bars.slice(32).reduce((s, v) => s + v, 0);
-    expect(lowSum).toBeGreaterThan(highSum * 5);
+    expect(lowSum).toBeGreaterThan(0.1);
+    expect(lowSum).toBeGreaterThan(highSum + 0.1);
   });
 
   it("silence produces all-near-zero bars", () => {