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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])
    };
  });
}
  
  /**
 * 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 

              
                const audioCtx = new AudioContext();
const audioPlayer = document.getElementById('audio');
const localAudioElement = document.getElementById('audioFileInput');
localAudioElement.addEventListener('change', loadLocalFile);
const canvas = document.getElementById('canvas'),
      ctx = canvas.getContext('2d'),
      container = document.getElementById('container');
const audioSource = audioCtx.createMediaElementSource(audioPlayer);
const analyser = audioCtx.createAnalyser();
const convolver = audioCtx.createConvolver();
analyser.fftSize = 32768; // maxes out FFT size
const dataArray = new Float32Array(analyser.fftSize);
let freqResponseArray = [],
    irResponseArray = [];
audioSource.connect(convolver);
convolver.connect(audioCtx.destination);
convolver.connect(analyser);
const wavToExport = new wavefile.WaveFile();

const visualizerSettings = {
  type: 'spectrum',
  fftSize: 4096,
  minFreq: 20,
  maxFreq: 20000,
  fscale: 'logarithmic',
  hzLinearFactor: 0,
  minDecibels: -90,
  maxDecibels: 0,
  freeze: false,
  showResponse: true,
  showLabels: true,
  showLabelsY: true,
  darkMode: false,
},
      eqSettings = {
        numBands: 24,
        minFreq: 20,
        maxFreq: 20000,
        fscale: 'bark',
        linearFactor: 0,
        irLength: 100,
        preamp: 0,
        irExportName: 'eq impulse',
        bitDepth: '32f',
        sampleRate: 48000,
        export: exportIR
      },
      visualizationType = [
        'spectrum',
        'waveform'
      ],
      fscaleSettings = [
        'bark',
        'erb',
        'mel',
        'linear',
        'logarithmic',
        'sinh',
        'shifted log',
        'nth root',
        'negative exponential'
      ],
      loader = {
        url: '',
        load: function() {
          audioPlayer.src = this.url;
          audioPlayer.play();
        },
        loadLocal: function() {
          localAudioElement.click();
        }
      };

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');
settings.add(visualizerSettings, 'type', visualizationType).name('Visualization type');
settings.add(visualizerSettings, 'minFreq', 0, 22050).name('Minimum frequency');
settings.add(visualizerSettings, 'maxFreq', 0, 22050).name('Maximum frequency');
settings.add(visualizerSettings, 'fscale', fscaleSettings).name('Frequency scale');
settings.add(visualizerSettings, 'hzLinearFactor', 0, 100).name('Hz linear factor');
settings.add(visualizerSettings, 'fftSize', 32, 32768, 1).name('FFT size');
settings.add(visualizerSettings, 'minDecibels', -120, 0).name('Lower amplitude range');
settings.add(visualizerSettings, 'maxDecibels', -120, 0).name('Higher amplitude range');
settings.add(visualizerSettings, 'freeze').name('Freeze analyser');
settings.add(visualizerSettings, 'showResponse').name('Show filter response');
settings.add(visualizerSettings, 'showLabels').name('Show horizontal-axis labels');
settings.add(visualizerSettings, 'showLabelsY').name('Show vertical-axis labels');
settings.add(visualizerSettings, 'darkMode').name('Dark mode');
let bandsFolder = gui.addFolder('Graphic equalizer');
let bands = [];
for (let i = 0; i < 32; i++) {
  bands[i] = {value: 0};
  bandsFolder.add(bands[i], 'value', -24, 24).name(`${i + 1} band`).onFinishChange(updateIR);
}
let eqSettingsFolder = gui.addFolder('Graphic EQ settings');
eqSettingsFolder.add(eqSettings, 'preamp', -24, 24).name('Preamp').onFinishChange(updateIR);
eqSettingsFolder.add(eqSettings, 'numBands', 2, bands.length, 1).name('Number of bands').onFinishChange(updateIR);
eqSettingsFolder.add(eqSettings, 'minFreq', 0, 22050).name('Minimum frequency range').onFinishChange(updateIR);
eqSettingsFolder.add(eqSettings, 'maxFreq', 0, 22050).name('Maximum frequency range').onFinishChange(updateIR);
eqSettingsFolder.add(eqSettings, 'fscale', fscaleSettings).name('Frequency scale').onFinishChange(updateIR);
eqSettingsFolder.add(eqSettings, 'linearFactor', 0, 1).name('Hz linear factor').onFinishChange(updateIR);
eqSettingsFolder.add(eqSettings, 'irLength', 20, 2000).name('Impulse response length').onFinishChange(updateIR);
const exportFolder = eqSettingsFolder.addFolder('Export as impulse response file');
exportFolder.add(eqSettings, 'sampleRate', 8000, 192000, 1).name('Sample rate');
exportFolder.add(eqSettings, 'bitDepth', {
  'Single-precision (float32)': '32f',
  'Double-precision (float64)': '64'
}).name('Bit depth');
exportFolder.add(eqSettings, 'irExportName').name('Impulse response file name');
exportFolder.add(eqSettings, 'export').name('Export as audio file');

function resizeCanvas() {
  const scale = devicePixelRatio;
  canvas.width = container.clientWidth*scale;
  canvas.height = container.clientHeight*scale;
}

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);
}
const test = map(0, 0, 1, -1, 1); // Smoke testing
updateIR();
visualize();
function visualize() {
  if (!visualizerSettings.freeze) {
    analyser.getFloatTimeDomainData(dataArray);
  }
  const fftData = [];
  let norm = 0;
  for (let i = 0; i < visualizerSettings.fftSize; i++) {
    const x = map(i, 0, visualizerSettings.fftSize, -1, 1),
          w = applyWindow(x, visualizerSettings.type === 'spectrum' ? 'hann' : 'rectangular'),
          magnitude = dataArray[i+analyser.fftSize-visualizerSettings.fftSize];
    norm += w;
    fftData[i] = magnitude * w;
  }
  
  const spectrum = visualizerSettings.type === 'spectrum' ? calcFFT(fftData.map(x => x*(fftData.length/norm))) : fftData,
        bgColor = visualizerSettings.darkMode ? '#000' : '#fff',
        fgColor = visualizerSettings.darkMode ? '#fff' : '#000';
  ctx.fillStyle = bgColor;
  ctx.strokeStyle = bgColor;
  ctx.fillRect(0, 0, canvas.width, canvas.height);
  ctx.fillStyle = fgColor;
  ctx.strokeStyle = fgColor;
  // Waveform and spectrum (FFT) visualization part
  ctx.beginPath();
  if (visualizerSettings.type === 'spectrum')
    spectrum.map((x, i) => {
      ctx.lineTo(map(fscale(fftBinToHertz(i, fftData.length, audioCtx.sampleRate), visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.minFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.maxFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), 0, canvas.width),
                 map(20*Math.log10(x), visualizerSettings.minDecibels, visualizerSettings.maxDecibels, canvas.height, 0));
    });
  else
    spectrum.map((x, i, arr) => {
      ctx.lineTo(i*canvas.width/arr.length, map(x, -1, 1, canvas.height, 0));
    });
  ctx.stroke();
  // Impulse response and frequency response part
  if (visualizerSettings.showResponse) {
    ctx.beginPath();
    if (visualizerSettings.type === 'spectrum')
      freqResponseArray.map((x, i) => {
        ctx.lineTo(map(fscale(fftBinToHertz(i, irResponseArray.length, audioCtx.sampleRate), visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.minFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.maxFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), 0, canvas.width),
                   map(20*Math.log10(x*irResponseArray.length/Math.sqrt(2)), -24, 24, canvas.height, 0));
      });
    else
      irResponseArray.map((x, i, arr) => {
        ctx.lineTo(i*canvas.width/arr.length, map(x, -1, 1, canvas.height, 0));
      });
    ctx.stroke();
  }
  // label part
  ctx.font = `${Math.trunc(10*devicePixelRatio)}px sans-serif`;
  ctx.textAlign = 'start';
  // Time-frequency label part
  if (visualizerSettings.showLabels) {
    ctx.globalAlpha = 0.5;
    ctx.setLineDash([]);
    if (visualizerSettings.type === 'spectrum') 
      [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 20000].map(x => {
        ctx.globalAlpha = 0.5;
        const label = (x >= 1000) ? `${x / 1000}kHz` : `${x}Hz`,
              posX = map(fscale(x, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.minFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.maxFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), 0, canvas.width);
        ctx.beginPath();
        ctx.lineTo(posX, canvas.height);
        ctx.lineTo(posX, 0);
        ctx.stroke();
        ctx.globalAlpha = 1;
        ctx.fillText(label, posX, canvas.height);
      });
    else {
      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10].map(x =>{
        ctx.globalAlpha = 0.5;
        const label = `${Math.round(map(x, 0, 10, spectrum.length, 1))} samples`,
              posX = map(x, 0, 10, 0, canvas.width);
        ctx.beginPath();
        ctx.lineTo(posX, canvas.height);
        ctx.lineTo(posX, 0);
        ctx.stroke();
        ctx.globalAlpha = 1;
        ctx.fillText(label, posX, canvas.height);
      });
      if (visualizerSettings.showResponse)
        [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10].map(x =>{
          ctx.globalAlpha = 0.5;
          const label = `${Math.round(map(x, 0, 10, irResponseArray.length, 1))} samples`,
                posX = map(x, 0, 10, 0, canvas.width);
          ctx.setLineDash([2, 4]);
          ctx.beginPath();
          ctx.lineTo(posX, canvas.height);
          ctx.lineTo(posX, 0);
          ctx.stroke();
          ctx.globalAlpha = 1;
          ctx.textAlign = 'end'
          ctx.fillText(label, posX, canvas.height);
        });
    }
    ctx.setLineDash([]);
    ctx.globalAlpha = 1;
    ctx.textAlign = 'start';
  }
  // Amplitude/decibel label part
  if (visualizerSettings.showLabelsY) {
    ctx.globalAlpha = 0.5;
    ctx.setLineDash([]);
    if (visualizerSettings.type === 'spectrum') {
      [0, -6, -12, -18, -24, -30, -36, -42, -48, -54, -60, -66, -72, -78, -84, -90].map(x => {
        ctx.globalAlpha = 0.5;
        const label = `${x}dB`,
              posY = map(x, visualizerSettings.minDecibels, visualizerSettings.maxDecibels, canvas.height, 0);
        ctx.beginPath();
        ctx.lineTo(0, posY);
        ctx.lineTo(canvas.width, posY);
        ctx.stroke();
        ctx.globalAlpha = 1;
        ctx.fillText(label, 0, posY);
      });
      if (visualizerSettings.showResponse)
        [24, 18, 12, 6, 0, -6, -12, -18, -24].map(x => {
          ctx.globalAlpha = 0.5;
          const label = `${x}dB`,
                posY = map(x, -24, 24, canvas.height, 0);
          ctx.setLineDash([2, 4]);
          ctx.beginPath();
          ctx.lineTo(0, posY);
          ctx.lineTo(canvas.width, posY);
          ctx.stroke();
          ctx.globalAlpha = 1;
          ctx.textAlign = 'end';
          ctx.fillText(label, canvas.width, posY);
        });
    }
    else
      [0, -6, -12, -18, -24, -Infinity].map(x => {
        ctx.globalAlpha = 0.5;
        const label = `${x}${isFinite(x) ? '' : ' '}dB`,
              posY = map(10 ** (x/20), -1, 1, canvas.height, 0);
        ctx.beginPath();
        ctx.lineTo(0, posY);
        ctx.lineTo(canvas.width, posY);
        ctx.stroke();
        // inverted part since waveform has negative polarity, since decibels is 20 * log10(abs(x))
        if (isFinite(x)) {
          ctx.beginPath();
          ctx.lineTo(0, canvas.height-posY);
          ctx.lineTo(canvas.width, canvas.height-posY);
          ctx.stroke();
        }
        ctx.globalAlpha = 1;
        ctx.fillText(label, 0, posY);
        if (isFinite(x))
          ctx.fillText(label, 0, canvas.height-posY);
      });
    ctx.setLineDash([]);
    ctx.globalAlpha = 1;
    ctx.textAlign = 'start'
  }
  requestAnimationFrame(visualize);
}

// additional functions
function updateIR() {
  const bufferSize = Math.round(eqSettings.irLength*audioCtx.sampleRate/1000/2) * 2,
        impulseResponse = audioCtx.createBuffer(1, bufferSize+1, audioCtx.sampleRate);
  freqResponseArray = [];
  irResponseArray = [];
  convolver.buffer = null;
  let impulseResponseData = calcEQResponse(eqSettings.numBands, bands.map(x => 10 ** ((x.value+eqSettings.preamp)/20)), eqSettings.minFreq, eqSettings.maxFreq, eqSettings.fscale, eqSettings.linearFactor, bufferSize, audioCtx.sampleRate);
  transform(impulseResponseData, impulseResponseData.map(x => 0));
  const firData = impulseResponse.getChannelData(0);
  for (let i = 0; i < firData.length; i++) {
    firData[i] = impulseResponseData[idxWrapOver(i, bufferSize)]/firData.length * 2 * applyWindow(map(i, 0, firData.length-1, -1, 1), 'hann');
    irResponseArray[i] = firData[i];
  }
  freqResponseArray = calcFFT(irResponseArray);
  convolver.normalize = false;
  convolver.buffer = impulseResponse;
}

function exportIR() {
  const sampleRate = eqSettings.sampleRate,
        bufferSize = Math.round(eqSettings.irLength*sampleRate/1000/2) * 2,
        impulseResponse = [],
        impulseResponseData = calcEQResponse(eqSettings.numBands, bands.map(x => 10 ** ((x.value+eqSettings.preamp)/20)), eqSettings.minFreq, eqSettings.maxFreq, eqSettings.fscale, eqSettings.linearFactor, bufferSize, sampleRate);
  transform(impulseResponseData, impulseResponseData.map(x => 0));
  for (let i = 0; i <= bufferSize; i++) {
    impulseResponse[i] = impulseResponseData[idxWrapOver(i, bufferSize)]/(bufferSize+1) * 2 * applyWindow(map(i, 0, bufferSize, -1, 1), 'hann');
  }
  wavToExport.fromScratch(1, eqSettings.sampleRate, eqSettings.bitDepth, impulseResponse);
  exportToAudioFile(wavToExport.toBuffer(), eqSettings.irExportName);
}

function calcEQResponse(N = 24, gains = [], minFreq = 20, maxFreq = 20000, scale = 'bark', linearFactor = 0.5, bufferSize = 4410, sampleRate = 44100) {
  let data = new Array(bufferSize).fill(0);
  for (let band = 0; band < N; band++) {
    const lowerBound = map(band-1, 0, N-1, fscale(minFreq, scale, linearFactor), fscale(maxFreq, scale, linearFactor)),
          higherBound = map(band+1, 0, N-1, fscale(minFreq, scale, linearFactor), fscale(maxFreq, scale, linearFactor)),
          type = band > 0 && band < N-1 ? 'bandpass' : (band > 0 ? 'highpass' : 'lowpass'),
          minIdx = type === 'bandpass' || type === 'highpass' ? (clamp(hertzToFFTBin(invFscale(lowerBound, scale, linearFactor), 'floor', bufferSize, sampleRate), 0, bufferSize/2)) : 0,
          maxIdx = type === 'bandpass' || type === 'lowpass' ? (clamp(hertzToFFTBin(invFscale(higherBound, scale, linearFactor), 'ceil', bufferSize, sampleRate), 0, bufferSize/2)) : bufferSize/2,
          magnitude = (gains[band] === undefined) ? 1 : gains[band];
    for (let i = minIdx; i <= maxIdx; i++) {
      let posX = i/bufferSize*sampleRate;
      posX = map(fscale(posX, scale, linearFactor), lowerBound, higherBound, -1, 1);
      const polarity = -(-1+2*(i%2)),
            isWithinBounds = Math.abs(i) <= 0 || Math.abs(i) >= bufferSize/2;
      data[i] += ((Math.abs(posX) <= 1 && ((Math.sign(posX) * (-1+(type === 'highpass')*2)) <= 0 || type === 'bandpass') ? applyWindow(posX, 'hann') : Math.max(Math.sign(posX) * (-1+(type === 'highpass')*2), 0) * (type !== 'bandpass'))*polarity) * magnitude * (1-isWithinBounds/2);
    }
  }
  return data;
}

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 '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 '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);
  }
}

function fscale(x, freqScale = 'logarithmic', freqSkew = 0.5) {
  switch(freqScale.toLowerCase()) {
    default:
      return x;
    case 'log':
    case 'logarithmic':
      return Math.log2(x);
    case 'mel':
      return Math.log2(1+x/700);
    case 'critical bands':
    case 'bark':
      return (26.81*x)/(1960+x)-0.53;
    case 'equivalent rectangular bandwidth':
    case 'erb':
      return Math.log2(1+0.00437*x);
    case 'sinh':
    case 'arcsinh':
    case 'asinh':
      return Math.asinh(x/(10 ** (freqSkew*4)));
    case 'shifted log':
    case 'shifted logarithmic':
      return Math.log2((10 ** (freqSkew*4))+x);
    case 'nth root':
      return x ** (1/(11-freqSkew*10));
    case 'negative exponential':
      return -(2 ** (-x/(2 ** (7+freqSkew*8))));
  }
}

function invFscale(x, freqScale = 'logarithmic', freqSkew = 0.5) {
  switch(freqScale.toLowerCase()) {
    default:
      return x;
    case 'log':
    case 'logarithmic':
      return 2 ** x;
    case 'mel':
      return 700 * ((2 ** x) - 1);
    case 'critical bands':
    case 'bark':
      return 1960 / (26.81/(x+0.53)-1);
    case 'equivalent rectangular bandwidth':
    case 'erb':
      return (1/0.00437) * ((2 ** x) - 1);
    case 'sinh':
    case 'arcsinh':
    case 'asinh':
      return Math.sinh(x)*(10 ** (freqSkew*4));
    case 'shifted log':
    case 'shifted logarithmic':
      return (2 ** x) - (10 ** (freqSkew*4));
    case 'nth root':
      return x ** ((11-freqSkew*10));
    case 'negative exponential':
      return -Math.log2(-x)*(2 ** (7+freqSkew*8));
  }
}

function exportToAudioFile(data, fileName) {
  const a = document.createElement('a'),
        blob = new Blob([data], {type: 'audio/wav'}),
        tempURL = URL.createObjectURL(blob);
  a.setAttribute('href', tempURL);
  a.setAttribute('download', `${fileName}.wav`);
  a.click();
  URL.revokeObjectURL(tempURL);
}
!
999px

Console