realtimeanalyser-fft-scaling.html

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This WPT test may be referenced by the following Test IDs:
- /webaudio/the-audio-api/the-analysernode-interface/realtimeanalyser-fft-scaling.html - WPT Dashboard Interop Dashboard

<!DOCTYPE html>

<html>

  <head>

    <title>

      realtimeanalyser-fft-scaling.html

    </title>

    <script src="/resources/testharness.js"></script>

    <script src="/resources/testharnessreport.js"></script>

  </head>

  <body>

    <div id="description"></div>

    <div id="console"></div>

    <script>

      // The number of analysers. We have analysers from size for each of the

      // possible sizes of 2^5 to 2^15 for a total of 11.

      const numberOfAnalysers = 11;

      const sampleRate = 44100;

      const nyquistFrequency = sampleRate / 2;

      // Frequency of the sine wave test signal.  Should be high enough so that

      // we get at least one full cycle for the 32-point FFT.  This should also

      // be such that the frequency should be exactly in one of the FFT bins for

      // each of the possible FFT sizes.

      const oscFrequency = nyquistFrequency / 16;

      // The actual peak values from each analyser.  Useful for examining the

      // actual peak values.

      const peakValue = new Array(numberOfAnalysers);

      // For a 0dBFS sine wave, we would expect the FFT magnitude to be 0dB as

      // well, but the analyzer node applies a Blackman window (to smooth the

      // estimate).  This reduces the energy of the signal so the FFT peak is

      // less than 0dB.  The threshold value given here was determined

      // experimentally.

//

      // See https://code.google.com/p/chromium/issues/detail?id=341596.

      const peakThreshold = [

        -14.43, -13.56, -13.56, -13.56, -13.56, -13.56, -13.56, -13.56, -13.56,

        -13.56, -13.56,

];

      function checkResult(order, analyser) {

        const index = order - 5;

        const fftSize = 1 << order;

        // We only need frequencyBinCount bins.

        const fftData = new Float32Array(fftSize);

        analyser.getFloatFrequencyData(fftData);

        // Compute the frequency bin that should contain the peak.

        const expectedBin =

            analyser.frequencyBinCount * (oscFrequency / nyquistFrequency);

        // Find the actual bin by finding the bin containing the peak.

        let actualBin = 0;

        peakValue[index] = -1000;

        for (let k = 0; k < analyser.frequencyBinCount; ++k) {

          if (fftData[k] > peakValue[index]) {

            actualBin = k;

            peakValue[index] = fftData[k];

        assert_equals(

            actualBin, expectedBin,

            `${(fftSize)}-point FFT peak position`);

        assert_greater_than_equal(

            peakValue[index], peakThreshold[index],

            `${fftSize}-point FFT peak value in dBFS`);

      // Run the tests for FFT sizes 2^5 through 2^15.

      function runTest(order) {

        const context = new OfflineAudioContext(1, 1 << order, sampleRate);

        const fftSize = 1 << order;

        // Use a sine wave oscillator as the reference source signal.

        const osc = new OscillatorNode(

            context, {type: 'sine', frequency: oscFrequency});

        // No smoothing to simplify the analysis of the result.

        const analyser = new AnalyserNode(context, {

          fftSize: fftSize,

          smoothingTimeConstant: 0,

});

        osc.connect(context.destination);

        osc.connect(analyser);

        osc.start();

        return context.startRendering().then(() => {

          checkResult(order, analyser);

});

      promise_test(async t => {

        for (let k = 5; k <= 15; ++k) {

          await runTest(k);

      }, 'FFT scaling tests — Test Scaling of FFT in AnalyserNode');

    </script>

  </body>

</html>