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HTML 

              
                <div id="container"><canvas id="canvas"></canvas></div>
<audio id="audio" controls crossorigin></audio>
<input id="audioFileInput" type="file" accept="audio/*">
<script>
  function map(x, min, max, targetMin, targetMax) {
    return (x - min) / (max - min) * (targetMax - targetMin) + targetMin;
  }
  
  function clamp(x, min, max) {
    return Math.min(Math.max(x, min), max);
  }
  
  function idxWrapOver(x, length) {
    return (x % length + length) % length;
  }
  // Hz and FFT bin conversion
function hertzToFFTBin(x, y = 'round', bufferSize = 4096, sampleRate = 44100) {
  const bin = x * bufferSize / sampleRate;
  let func = y;
  
  if (!['floor','ceil','trunc'].includes(func))
    func = 'round'; // always use round if you specify an invalid/undefined value
  
  return Math[func](bin);
}

function fftBinToHertz(x, bufferSize = 4096, sampleRate = 44100) {
  return x * sampleRate / bufferSize;
}
  

// Calculate the FFT
function calcFFT(input) {
  let fft = input.map(x => x);
  let fft2 = input.map(x => x);
  transform(fft, fft2);
  let output = new Array(Math.round(fft.length/2)).fill(0);
  for (let i = 0; i < output.length; i++) {
    output[i] = Math.hypot(fft[i], fft2[i])/(fft.length);
  }
  return output;
}

function calcComplexFFT(input) {
  let fft = input.map(x => x);
  let fft2 = input.map(x => x);
  transform(fft, fft2);
  return input.map((_, i, arr) => {
    return {
      re: fft[i]/(arr.length/2),
      im: fft2[i]/(arr.length/2),
      magnitude: Math.hypot(fft[i], fft2[i])/(arr.length/2),
      phase: Math.atan2(fft2[i], fft[i])
    };
  });
}
  
function calcComplexInputFFT(real, imag) {
  if (real.length !== imag.length)
    return [];
  const fft1 = real.map(x => x),
        fft2 = imag.map(x => x);
  transform(fft1, fft2);
  return real.map((_, i, arr) => {
    return {
      re: fft1[i]/arr.length,
      im: fft2[i]/arr.length,
      magnitude: Math.hypot(fft1[i], fft2[i])/arr.length,
      phase: Math.atan2(fft2[i], fft1[i])
    }
  });
}
  
  /**
 * FFT and convolution (JavaScript)
 * 
 * Copyright (c) 2017 Project Nayuki. (MIT License)
 * https://www.nayuki.io/page/free-small-fft-in-multiple-languages
 */

/* 
 * Computes the discrete Fourier transform (DFT) of the given complex vector, storing the result back into the vector.
 * The vector can have any length. This is a wrapper function.
 */
function transform(real, imag) {
	const n = real.length;
	if (n != imag.length)
		throw "Mismatched lengths";
	if (n <= 0)
		return;
	else if ((2 ** Math.trunc(Math.log2(n))) === n)  // Is power of 2
		transformRadix2(real, imag);
	else  // More complicated algorithm for arbitrary sizes
		transformBluestein(real, imag);
}


/* 
 * Computes the inverse discrete Fourier transform (IDFT) of the given complex vector, storing the result back into the vector.
 * The vector can have any length. This is a wrapper function. This transform does not perform scaling, so the inverse is not a true inverse.
 */
function inverseTransform(real, imag) {
	transform(imag, real);
}


/* 
 * Computes the discrete Fourier transform (DFT) of the given complex vector, storing the result back into the vector.
 * The vector's length must be a power of 2. Uses the Cooley-Tukey decimation-in-time radix-2 algorithm.
 */
function transformRadix2(real, imag) {
	// Length variables
	const n = real.length;
	if (n != imag.length)
		throw "Mismatched lengths";
	if (n <= 1)  // Trivial transform
		return;
	const logN = Math.log2(n);
	if ((2 ** Math.trunc(logN)) !== n)
		throw "Length is not a power of 2";
	
	// Trigonometric tables
	let cosTable = new Array(n / 2);
	let sinTable = new Array(n / 2);
	for (let i = 0; i < n / 2; i++) {
		cosTable[i] = Math.cos(2 * Math.PI * i / n);
		sinTable[i] = Math.sin(2 * Math.PI * i / n);
	}
	
	// Bit-reversed addressing permutation
	for (let i = 0; i < n; i++) {
		let j = reverseBits(i, logN);
		if (j > i) {
			let temp = real[i];
			real[i] = real[j];
			real[j] = temp;
			temp = imag[i];
			imag[i] = imag[j];
			imag[j] = temp;
		}
	}
	
	// Cooley-Tukey decimation-in-time radix-2 FFT
	for (let size = 2; size <= n; size *= 2) {
		let halfsize = size / 2;
		let tablestep = n / size;
		for (let i = 0; i < n; i += size) {
			for (let j = i, k = 0; j < i + halfsize; j++, k += tablestep) {
				const l = j + halfsize;
				const tpre =  real[l] * cosTable[k] + imag[l] * sinTable[k];
				const tpim = -real[l] * sinTable[k] + imag[l] * cosTable[k];
				real[l] = real[j] - tpre;
				imag[l] = imag[j] - tpim;
				real[j] += tpre;
				imag[j] += tpim;
			}
		}
	}
	
	// Returns the integer whose value is the reverse of the lowest 'bits' bits of the integer 'x'.
	function reverseBits(x, bits) {
		let y = 0;
		for (let i = 0; i < bits; i++) {
			y = (y << 1) | (x & 1);
			x >>>= 1;
		}
		return y;
	}
}


/* 
 * Computes the discrete Fourier transform (DFT) of the given complex vector, storing the result back into the vector.
 * The vector can have any length. This requires the convolution function, which in turn requires the radix-2 FFT function.
 * Uses Bluestein's chirp z-transform algorithm.
 */
function transformBluestein(real, imag) {
	// Find a power-of-2 convolution length m such that m >= n * 2 + 1
	const n = real.length;
	if (n != imag.length)
		throw "Mismatched lengths";
	const m = 2 ** Math.trunc(Math.log2(n*2)+1);
	
	// Trignometric tables
	let cosTable = new Array(n);
	let sinTable = new Array(n);
	for (let i = 0; i < n; i++) {
		let j = i * i % (n * 2);  // This is more accurate than j = i * i
		cosTable[i] = Math.cos(Math.PI * j / n);
		sinTable[i] = Math.sin(Math.PI * j / n);
	}
	
	// Temporary vectors and preprocessing
	let areal = newArrayOfZeros(m);
	let aimag = newArrayOfZeros(m);
	for (let i = 0; i < n; i++) {
		areal[i] =  real[i] * cosTable[i] + imag[i] * sinTable[i];
		aimag[i] = -real[i] * sinTable[i] + imag[i] * cosTable[i];
	}
	let breal = newArrayOfZeros(m);
	let bimag = newArrayOfZeros(m);
	breal[0] = cosTable[0];
	bimag[0] = sinTable[0];
	for (let i = 1; i < n; i++) {
		breal[i] = breal[m - i] = cosTable[i];
		bimag[i] = bimag[m - i] = sinTable[i];
	}
	
	// Convolution
	let creal = new Array(m);
	let cimag = new Array(m);
	convolveComplex(areal, aimag, breal, bimag, creal, cimag);
	
	// Postprocessing
	for (let i = 0; i < n; i++) {
		real[i] =  creal[i] * cosTable[i] + cimag[i] * sinTable[i];
		imag[i] = -creal[i] * sinTable[i] + cimag[i] * cosTable[i];
	}
}


/* 
 * Computes the circular convolution of the given real vectors. Each vector's length must be the same.
 */
function convolveReal(x, y, out) {
	const n = x.length;
	if (n != y.length || n != out.length)
		throw "Mismatched lengths";
	convolveComplex(x, newArrayOfZeros(n), y, newArrayOfZeros(n), out, newArrayOfZeros(n));
}


/* 
 * Computes the circular convolution of the given complex vectors. Each vector's length must be the same.
 */
function convolveComplex(xreal, ximag, yreal, yimag, outreal, outimag) {
	const n = xreal.length;
	if (n != ximag.length || n != yreal.length || n != yimag.length
			|| n != outreal.length || n != outimag.length)
		throw "Mismatched lengths";
	
	xreal = xreal.slice();
	ximag = ximag.slice();
	yreal = yreal.slice();
	yimag = yimag.slice();
	transform(xreal, ximag);
	transform(yreal, yimag);
	
	for (let i = 0; i < n; i++) {
		const temp = xreal[i] * yreal[i] - ximag[i] * yimag[i];
		ximag[i] = ximag[i] * yreal[i] + xreal[i] * yimag[i];
		xreal[i] = temp;
	}
	inverseTransform(xreal, ximag);
	
	for (let i = 0; i < n; i++) {  // Scaling (because this FFT implementation omits it)
		outreal[i] = xreal[i] / n;
		outimag[i] = ximag[i] / n;
	}
}


function newArrayOfZeros(n) {
	let result = new Array(n).fill(0);
	return result;
}
</script>
!

CSS 

              
                body {
  margin: 0;
  overflow: hidden;
}

audio {
  display: inline-block;
  width: 100%;
  height: 40px;
}

canvas {
  display: block;
  width: 100%;
}

#container {
  height: calc( 100vh - 40px );
}

#upload {
  display: none;
}
!

JS 

              
                // necessary parts for audio context and audio elements respectively
const audioCtx = new AudioContext();
const audioPlayer = document.getElementById('audio');
const localAudioElement = document.getElementById('audioFileInput');
localAudioElement.addEventListener('change', loadLocalFile);
// canvas is for displaying visuals
const canvas = document.getElementById('canvas'),
      ctx = canvas.getContext('2d'),
      container = document.getElementById('container');
const audioSource = audioCtx.createMediaElementSource(audioPlayer);
const analyser = audioCtx.createAnalyser();
analyser.fftSize = 32768; // maxes out FFT size
const dataArray = new Float32Array(analyser.fftSize);
// variables
const fifoBuffers = [],
      smoothed = [],
      peaks = [],
      holds = [];
let fifoIdx = 0;
/*
const currentSpectrum = [],
      peaks = [],
      peakHolds = [],
      peakAccels = [];
*/
const delay = audioCtx.createDelay();
audioSource.connect(delay);
delay.connect(audioCtx.destination);
//audioSource.connect(audioCtx.destination);
audioSource.connect(analyser);

const visualizerSettings = {
  fftSize: 16384,
  fifoLength: 30,
  fifoDomain: 'linear',
  calibrationDomain: 'linear',
  smoothingTimeConstant: 95,
  peakDecayTimeConstant: 99,
  holdTime: 180,
  resetAverage: resetFIFO,
  showCrest: true,
  showPeaks: true,
  showAverage: true,
  showCurrent: true,
  showCalibration: true,
  freeze: false,
  darkMode: true,
  compensateDelay: true
},
      placeholderListData = {
        'Option 1': 'one',
        'Option 2': 'two'
      }, // useful for multiple options sharing dropdown menu options
      averagingDomains = {
        'Linear': 'linear',
        'Squared': 'rms',
        'Logarithmic': 'log'
      },
      loader = {
        url: '',
        load: function() {
          audioPlayer.src = this.url;
          audioPlayer.play();
        },
        loadLocal: function() {
          localAudioElement.click();
        },
        toggleFullscreen: _ => {
          if (document.fullscreenElement === canvas)
            document.exitFullscreen();
          else
            canvas.requestFullscreen();
        }
      };
// dat.GUI for quick customization
let gui = new dat.GUI();
gui.add(loader, 'url').name('URL');
gui.add(loader, 'load').name('Load');
gui.add(loader, 'loadLocal').name('Load from local device');
let settings = gui.addFolder('Visualization settings');
// FFT size can be non-power of 2 because we use the FFT library that supports non-power of two data length
settings.add(visualizerSettings, 'fftSize', 32, 32768, 1).name('FFT size').onChange(resetFIFO);
// The additional parameters goes here
settings.add(visualizerSettings, 'fifoLength', 1, 240, 1).name('FIFO averaging length').onChange(resetFIFO);
settings.add(visualizerSettings, 'fifoDomain', averagingDomains).name('FIFO averaging domain');
settings.add(visualizerSettings, 'smoothingTimeConstant', 0, 100).name('Main spectrum decay rate');
settings.add(visualizerSettings, 'peakDecayTimeConstant', 0, 100).name('Peak decay rate');
settings.add(visualizerSettings, 'holdTime', 0, 240).name('Peak hold (frames)');
settings.add(visualizerSettings, 'resetAverage').name('Reset FIFO averaging');
settings.add(visualizerSettings, 'showPeaks').name('Show peak spectrum');
settings.add(visualizerSettings, 'showAverage').name('Show average spectrum');
settings.add(visualizerSettings, 'showCurrent').name('Show current spectrum');
settings.add(visualizerSettings, 'showCrest').name('Show crest spectrum');
settings.add(visualizerSettings, 'showCalibration').name('Show calibration line');
settings.add(visualizerSettings, 'calibrationDomain', averagingDomains).name('Calibration line calculation domain');
// another parameters at the end
settings.add(visualizerSettings, 'freeze').name('Freeze analyzer');
settings.add(visualizerSettings, 'darkMode').name('Dark mode');
settings.add(visualizerSettings, 'compensateDelay').name('Compensate for delay');
gui.add(loader, 'toggleFullscreen').name('Toggle fullscreen mode');

function resizeCanvas() {
  const scale = devicePixelRatio,
        isFullscreen = document.fullscreenElement === canvas;
  canvas.width = (isFullscreen ? innerWidth : container.clientWidth)*scale;
  canvas.height = (isFullscreen ? innerHeight : container.clientHeight)*scale;
}
// additional function used by settings with onChange property
function resetFIFO() {
  smoothed.length = 0;
  fifoBuffers.length = 0;
  peaks.length = 0;
  holds.length = 0;
  fifoIdx = 0;
}

addEventListener('click', () => {
  if (audioCtx.state == 'suspended')
    audioCtx.resume();
});
addEventListener('resize', resizeCanvas);
resizeCanvas();

function loadLocalFile(event) {
  const file = event.target.files[0],
        reader = new FileReader();
  reader.onload = (e) => {
    audioPlayer.src = e.target.result;
    audioPlayer.play();
  };

  reader.readAsDataURL(file);
}

visualize();
function visualize() {
  delay.delayTime.value = (visualizerSettings.fftSize / audioCtx.sampleRate) * visualizerSettings.compensateDelay;
  if (!visualizerSettings.freeze) {
    // we use getFloatTimeDomainData (which is PCM data that is gathered, just like vis_stream::get_chunk_absolute() in foobar2000 SDK)
    analyser.getFloatTimeDomainData(dataArray);
  }
  const fftData = new Array(visualizerSettings.fftSize);
  let norm = 0; // we can use a variable called norm to compensate for gain changes incurred by a window function
  for (let i = 0; i < visualizerSettings.fftSize; i++) {
    const magnitude = dataArray[i+analyser.fftSize-visualizerSettings.fftSize],
          w = applyWindow(map(i, 0, visualizerSettings.fftSize, -1, 1), 'hann', 1, true, 0);
    fftData[i] = magnitude * w;
    norm += w;
  }
  const spectrumData = calcComplexFFT(fftData.map(x => x*fftData.length/norm/Math.SQRT2));
  const fgColor = visualizerSettings.darkMode ? '#fff' : '#000',
        bgColor = visualizerSettings.darkMode ? '#000' : '#fff';
  ctx.fillStyle = bgColor;
  ctx.fillRect(0, 0, canvas.width, canvas.height);
  //ctx.fillStyle = fgColor;
  //ctx.strokeStyle = fgColor;
  // fifo (first-in, first-out) averaging
  const fifoLength = visualizerSettings.fifoLength,
        crestSpectrum = new Array(spectrumData.length);
  let calibrationValue = 0;
  fifoBuffers.length = spectrumData.length;
  smoothed.length = spectrumData.length;
  peaks.length = spectrumData.length;
  holds.length = spectrumData.length;
  for (let i = 0; i < spectrumData.length; i++) {
    if (fifoBuffers[i] === undefined)
      fifoBuffers[i] = new Array(fifoLength);
    else
      fifoBuffers[i].length = fifoLength;
    fifoBuffers[i][fifoIdx] = spectrumData[i].magnitude;
    smoothed[i] = isFinite(smoothed[i]) ? Math.max(smoothed[i]*visualizerSettings.smoothingTimeConstant/100, spectrumData[i].magnitude) : spectrumData[i].magnitude;
    if (spectrumData[i].magnitude >= peaks[i] || !isFinite(peaks[i])) {
      peaks[i] = spectrumData[i].magnitude;
      holds[i] = visualizerSettings.holdTime;
    }
    else if (holds[i] > 0)
      holds[i]--;
    else
      peaks[i] *= visualizerSettings.peakDecayTimeConstant / 100;
  }
  fifoIdx = idxWrapOver(fifoIdx+1, fifoLength);
  ctx.lineWidth = 1;
  ctx.fillStyle = '#00f';
  ctx.strokeStyle = ctx.fillStyle;
  if (visualizerSettings.showPeaks) {
    ctx.beginPath();
    for (let i = 0; i < peaks.length; i++) {
      const x = peaks[i];
      // log frequency scale
      ctx.lineTo(map(Math.log2(fftBinToHertz(i, visualizerSettings.fftSize, audioCtx.sampleRate)), Math.log2(20), Math.log2(20000), 0, canvas.width), map(20*Math.log10(x), -100, 0, canvas.height, 0));
    }
    ctx.stroke();
  }
  ctx.fillStyle = fgColor;
  ctx.strokeStyle = fgColor;
  if (visualizerSettings.showCurrent) {
    ctx.beginPath();
    for (let i = 0; i < smoothed.length; i++) {
      const x = smoothed[i];
      // log frequency scale
      ctx.lineTo(map(Math.log2(fftBinToHertz(i, visualizerSettings.fftSize, audioCtx.sampleRate)), Math.log2(20), Math.log2(20000), 0, canvas.width), map(20*Math.log10(x), -100, 0, canvas.height, 0));
    }
    ctx.stroke();
  }
  ctx.lineWidth = 1;
  ctx.fillStyle = '#569CFF'//'#569CD6';
  ctx.strokeStyle = ctx.fillStyle;
  ctx.beginPath();
  for (let i = 0; i < fifoBuffers.length; i++) {
    const avg = fifoBuffers[i].reduce((acc, curr) => {
      const current = isFinite(curr) ? curr : 0;
      switch (visualizerSettings.fifoDomain) {
        case 'rms':
          return acc + current ** 2;
        case 'log':
          return acc + 20*Math.log10(current);
        default:
          return acc + current;
      }
    }, 0),
          smoothedPeak = fifoBuffers[i].reduce((acc, curr) => Math.max(acc, isFinite(curr) ? curr : 0), 0); // needed for calculating crest spectrum
    let x = avg;
    switch (visualizerSettings.fifoDomain) {
      case 'rms':
        x = Math.sqrt(avg/fifoLength);
        break;
      case 'log':
        x = 10 ** (avg/fifoLength/20);
        break;
      default:
        x /= fifoLength;
    }
    crestSpectrum[i] = smoothedPeak/x;
    // log frequency scale
    if (visualizerSettings.showAverage)
      ctx.lineTo(map(Math.log2(fftBinToHertz(i, visualizerSettings.fftSize, audioCtx.sampleRate)), Math.log2(20), Math.log2(20000), 0, canvas.width), map(20*Math.log10(x), -100, 0, canvas.height, 0));
    // calculating a calibration line
    switch (visualizerSettings.calibrationDomain) {
      case 'rms':
        calibrationValue += x ** 2;
        break;
      case 'log':
        calibrationValue += 20*Math.log10(x);
        break;
      default:
        calibrationValue += x;
    }
  }
  ctx.stroke();
  switch (visualizerSettings.calibrationDomain) {
    case 'rms':
      calibrationValue = Math.sqrt(calibrationValue/fifoBuffers.length);
      break;
    case 'log':
      calibrationValue = 10 ** (calibrationValue/fifoBuffers.length/20);
      break;
    default:
      calibrationValue /= fifoBuffers.length;
  }
  if (visualizerSettings.showCrest) {
    ctx.fillStyle = '#f00';
    ctx.strokeStyle = ctx.fillStyle;
    ctx.beginPath();
    for (let i = 0; i < crestSpectrum.length; i++) {
      const x = crestSpectrum[i];
      // log frequency scale
      ctx.lineTo(map(Math.log2(fftBinToHertz(i, visualizerSettings.fftSize, audioCtx.sampleRate)), Math.log2(20), Math.log2(20000), 0, canvas.width), map(20*Math.log10(x), 0, 100, canvas.height, 0));
    }
    ctx.stroke();
  }
  ctx.fillStyle = '#0f0';
  ctx.strokeStyle = ctx.fillStyle;
  if (visualizerSettings.showCalibration) {
    ctx.beginPath();
    ctx.lineTo(0, map(20*Math.log10(calibrationValue), -100, 0, canvas.height, 0));
    ctx.lineTo(canvas.width, map(20*Math.log10(calibrationValue), -100, 0, canvas.height, 0));
    ctx.stroke();
  }
  requestAnimationFrame(visualize);
}
// and here's the additional functions that we can need for this visualization
function applyWindow(posX, windowType = 'Hann', windowParameter = 1, truncate = true, windowSkew = 0) {
  let x = windowSkew > 0 ? ((posX/2-0.5)/(1-(posX/2-0.5)*10*(windowSkew ** 2)))/(1/(1+10*(windowSkew ** 2)))*2+1 :
                           ((posX/2+0.5)/(1+(posX/2+0.5)*10*(windowSkew ** 2)))/(1/(1+10*(windowSkew ** 2)))*2-1;
  
  if (truncate && Math.abs(x) > 1)
    return 0;
  
  switch (windowType.toLowerCase()) {
    default:
      return 1;
    case 'hanning':
    case 'cosine squared':
    case 'hann':
      return Math.cos(x*Math.PI/2) ** 2;
    case 'raised cosine':
    case 'hamming':
      return 0.54 + 0.46 * Math.cos(x*Math.PI);
    case 'power of sine':
      return Math.cos(x*Math.PI/2) ** windowParameter;
    case 'circle':
    case 'power of circle':
      return Math.sqrt(1 - (x ** 2)) ** windowParameter;
    case 'tapered cosine':
    case 'tukey':
      return Math.abs(x) <= 1-windowParameter ? 1 : 
      (x > 0 ? 
       (-Math.sin((x-1)*Math.PI/windowParameter/2)) ** 2 :
       Math.sin((x+1)*Math.PI/windowParameter/2) ** 2);
    case 'blackman':
      return 0.42 + 0.5 * Math.cos(x*Math.PI) + 0.08 * Math.cos(x*Math.PI*2);
    case 'nuttall':
      return 0.355768 + 0.487396 * Math.cos(x*Math.PI) + 0.144232 * Math.cos(2*x*Math.PI) + 0.012604 * Math.cos(3*x*Math.PI);
    case 'flat top':
    case 'flattop':
      return 0.21557895 + 0.41663158 * Math.cos(x*Math.PI) + 0.277263158 * Math.cos(2*x*Math.PI) + 0.083578947 * Math.cos(3*x*Math.PI) + 0.006947368 * Math.cos(4*x*Math.PI);
    case 'kaiser':
      return Math.cosh(Math.sqrt(1-(x ** 2))*(windowParameter ** 2))/Math.cosh(windowParameter ** 2);
    case 'gauss':
    case 'gaussian':
      return Math.exp(-(windowParameter ** 2)*(x ** 2));
    case 'cosh':
    case 'hyperbolic cosine':
      return Math.E ** (-(windowParameter ** 2)*(Math.cosh(x)-1));
    case 'bartlett':
    case 'triangle':
    case 'triangular':
      return 1 - Math.abs(x);
    case 'poisson':
    case 'exponential':
      return Math.exp(-Math.abs(x * (windowParameter ** 2)));
    case 'hyperbolic secant':
    case 'sech':
      return 1/Math.cosh(x * (windowParameter ** 2));
    case 'quadratic spline':
      return Math.abs(x) <= 0.5 ? -((x*Math.sqrt(2)) ** 2)+1 : (Math.abs(x*Math.sqrt(2))-Math.sqrt(2)) ** 2;
    case 'parzen':
      return Math.abs(x) > 0.5 ? -2 * ((-1 + Math.abs(x)) ** 3) : 1 - 24 * (Math.abs(x/2) ** 2) + 48 * (Math.abs(x/2) ** 3);
    case 'welch':
      return 1 - (x ** 2);
    case 'ogg':
    case 'vorbis':
      return Math.sin(Math.PI/2 * Math.cos(x*Math.PI/2) ** 2);
    case 'cascaded sine':
    case 'cascaded cosine':
    case 'cascaded sin':
    case 'cascaded cos':
      return 1 - Math.sin(Math.PI/2 * Math.sin(x*Math.PI/2) ** 2);
  }
}

/*navigator.mediaDevices.getUserMedia({
  audio: {
    noiseCancellation: false,
    echoCancellation: false,
    autoGainControl: false
  },
  video: false
}).then((stream) => {
  const audioStream = audioCtx.createMediaStreamSource(stream);
  //audioStream.connect(splitter);
  audioStream.connect(analyser);
}).catch((err) => {
  console.log(err);
});*/
!
999px

Console