data: real fft

src/data.mjs

@@ -41,12 +41,16 @@ export default class Data {
 
   sample(freq) {
     let presence = true;
+    let noise = Math.random() * 0.4;
 
     // E6=1318
     // A1=55
     if (!freq) {
       freq = Math.pow(2, Math.random() * 4.7) * 55;
       presence = Math.random() > 0.5;
+      if (!presence) {
+        noise = 1;
+      }
     }
     const f = freq / this.sampleRate;
     const phase = Math.random();
@@ -70,18 +74,17 @@ export default class Data {
       this.normalize(this.fftIn);
     }
 
-    const noise = Math.random() * 0.5;
-    for (let t = 0; t < this.fftIn.length; t++) {
-      this.fftIn[t] = this.fftIn[t] * (1 - noise) + Math.random() * noise;
-    }
-    this.normalize(this.fftIn);
-
     this.fft.realTransform(this.fftOut, this.fftIn);
+    for (let i = 0; i < this.fftSize; i += 2) {
+      this.fftOut[i >>> 1] = Math.sqrt(
+        this.fftOut[i] ** 2 + this.fftOut[i + 1] ** 2) * (1 - noise) +
+        Math.random() * noise;
+    }
 
     return {
       freq: presence ? freq : 440,
       presence,
-      fft: this.fftOut.slice(0, this.fftSize),
+      fft: this.fftOut.slice(0, this.fftSize >>> 1),
     };
   }
 }

src/train.mjs

@@ -34,7 +34,7 @@ async function main() {
   const name = '2048-32x4-1';
 
   model.add(tf.layers.dense({
-    inputShape: [ data.fftSize ],
+    inputShape: [ data.fftSize >>> 1 ],
     units: 32,
     activation: 'relu',
   }));