static getFrequencies()

in 9-realtime/openai-realtime-console-example/src/lib/wavtools/lib/analysis/audio_analysis.js [32:86]
54 lines of code
10 McCabe index (conditional complexity)

  static getFrequencies(
    analyser,
    sampleRate,
    fftResult,
    analysisType = 'frequency',
    minDecibels = -100,
    maxDecibels = -30,
  ) {
    if (!fftResult) {
      fftResult = new Float32Array(analyser.frequencyBinCount);
      analyser.getFloatFrequencyData(fftResult);
    }
    const nyquistFrequency = sampleRate / 2;
    const frequencyStep = (1 / fftResult.length) * nyquistFrequency;
    let outputValues;
    let frequencies;
    let labels;
    if (analysisType === 'music' || analysisType === 'voice') {
      const useFrequencies =
        analysisType === 'voice' ? voiceFrequencies : noteFrequencies;
      const aggregateOutput = Array(useFrequencies.length).fill(minDecibels);
      for (let i = 0; i < fftResult.length; i++) {
        const frequency = i * frequencyStep;
        const amplitude = fftResult[i];
        for (let n = useFrequencies.length - 1; n >= 0; n--) {
          if (frequency > useFrequencies[n]) {
            aggregateOutput[n] = Math.max(aggregateOutput[n], amplitude);
            break;
          }
        }
      }
      outputValues = aggregateOutput;
      frequencies =
        analysisType === 'voice' ? voiceFrequencies : noteFrequencies;
      labels =
        analysisType === 'voice' ? voiceFrequencyLabels : noteFrequencyLabels;
    } else {
      outputValues = Array.from(fftResult);
      frequencies = outputValues.map((_, i) => frequencyStep * i);
      labels = frequencies.map((f) => `${f.toFixed(2)} Hz`);
    }
    // We normalize to {0, 1}
    const normalizedOutput = outputValues.map((v) => {
      return Math.max(
        0,
        Math.min((v - minDecibels) / (maxDecibels - minDecibels), 1),
      );
    });
    const values = new Float32Array(normalizedOutput);
    return {
      values,
      frequencies,
      labels,
    };
  }