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<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, full = false) {
let fft = input.map(x => x);
let fft2 = input.map(x => x);
transform(fft, fft2);
let output = new Array(Math.round(fft.length/(2-full))).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, includeImag = false) {
let fft = input.map(x => x*Math.sqrt(1-includeImag));
let fft2 = input.map(x => x*includeImag);
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>
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;
}
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');
// necessary for spectrogram visualization
const auxCanvas = new OffscreenCanvas(0, 0),
auxCtx = auxCanvas.getContext('2d');
// audio part
const audioSource = audioCtx.createMediaElementSource(audioPlayer);
const analyser = audioCtx.createAnalyser(),
analyserL = audioCtx.createAnalyser(),
analyserR = audioCtx.createAnalyser();
analyser.fftSize = 32768; // maxes out FFT size
analyserL.fftSize = analyser.fftSize;
analyserR.fftSize = analyser.fftSize;
const dataArray = new Float32Array(analyser.fftSize),
dataArrayL = new Float32Array(analyserL.fftSize),
dataArrayR = new Float32Array(analyserR.fftSize);
let staticSpectrogramIdx = 0;
// DelayNode (optional to mimic reaction time for non-realtime visualizations or even foobar2000 visualizations)
const delay = audioCtx.createDelay(),
splitter = audioCtx.createChannelSplitter(2); // only work well for stereo signal, not sure how it works on the surround sound
audioSource.connect(delay);
delay.connect(audioCtx.destination);
//audioSource.connect(audioCtx.destination);
audioSource.connect(analyser);
audioSource.connect(splitter);
splitter.connect(analyserL, 0);
splitter.connect(analyserR, 1);
const visualizerSettings = {
inputSize: 4096,
fftSize: 4096,
minFreq: 20,
maxFreq: 20000,
fscale: 'logarithmic',
windowFunction: 'hann',
windowParameter: 1,
windowSkew: 0,
useNC: false,
ncDistance: 1,
hzLinearFactor: 0,
minDecibels: -90,
maxDecibels: 0,
useDecibels: true,
gamma: 1,
useAbsolute: true,
decoupleAmplitudeFromSpectrum: false,
altMinDecibels: -90,
altMaxDecibels: 0,
altUseDecibels: true,
altGamma: 1,
altUseAbsolute: true,
equalizeAmount: 0,
equalizeOffset: 44100,
equalizeDepth: 1024,
slope: 0,
slopeOffset: 1000,
weightingAmount: 0,
weightingType: 'k',
slopeFunctionsOffset: 1,
channelMode: 'mono',
treatAsComplex: false,
freeze: false,
// labels part
showLabels: true,
showLabelsY: true,
amplitudeLabelInterval: 6,
showDC: true,
showNyquist: true,
mirrorLabels: true,
labelTextAlign: 'start',
labelTextBaseline: 'alphabetic',
labelTextBaseline2: 'alphabetic',
// grid part
showLabels2: true,
showLabelsY2: true,
labelMode2: 'decade',
showDC2: true,
showNyquist2: true,
showBothYLabels: true,
alternatingGridPattern: true,
spectrogramExtendGrid: false,
diffLabels: false,
labelMode: 'decade',
labelTuning: 440,
// drawing part
useGradient: false,
alternateColor: false,
drawMode: 'stroke',
lowDetail: true,
useBars: false,
barSpacing: 1,
showStrokeRectAsBars: false,
lineWidth: 1,
lineJoin: 'miter',
miterLimit: 10,
darkMode: false,
compensateDelay: true,
display: 'spectrum',
clearSpectrogram: resizeCanvas
},
drawModes = {
'Line': 'stroke',
'Fill': 'fill',
'Both': 'both'
},
displayModes = {
'Spectrum': 'spectrum',
'Spectrogram': 'spectrogram',
'Static spectrogram': 'static',
'Spectrum and spectrogram': 'both'
},
windowFunctionSettings = {
'Rectangular': 'rectangular',
'Triangular (Bartlett)': 'triangular',
'Quadratic': 'quadratic spline',
'Parzen': 'parzen',
'Welch': 'welch',
'Power of sine': 'power of sine',
'Power of circle': 'circle',
'Tukey (tapered cosine)': 'tukey',
'Vorbis': 'vorbis',
'Cascaded sine': 'cascaded sine',
'Hann': 'hann',
'Hamming': 'hamming',
'Blackman': 'blackman',
'Nuttall': 'nuttall',
'Flat top': 'flattop',
'Gaussian': 'gauss',
'Hyperbolic cosine': 'cosh',
'Hyperbolic cosine 2': 'cosh 2',
'Kaiser': 'kaiser',
'Poisson': 'exponential',
'Hyperbolic secant': 'sech',
'Galss': 'galss', // Name derived from a particular program name (Aimp Galss Player) in Titanic Tools that pre-installed on Windows 7 Titanic Edition bootleg
'Glizzy': 'glizzy'
},
fscaleSettings = {
'Bark': 'bark',
'ERB': 'erb',
'Cams': 'cam',
'Mel (AIMP)': 'mel',
'Linear': 'linear',
'Logarithmic': 'logarithmic',
'Hyperbolic sine': 'sinh',
'Shifted logarithmic': 'shifted log',
'Nth root': 'nth root',
'Negative exponential': 'negative exponential',
'Adjustable Bark': 'adjustable bark',
'Period': 'period'
},
labelModes = {
'Decades': 'decade',
'Decades (coarse)': 'decade 2',
'Decades (without minor gridlines)': 'decade 3',
'Octaves': 'octave',
'Powers of two': 'powers of two',
'Notes': 'note',
'Critical bands': 'bark',
'Linear': 'linear'
},
channelModes = {
'Mono': 'mono',
'Stereo': 'stereo',
'Mid/Side': 'ms',
'L/R and M/S': 'both'
},
weightingTypes = {
'A': 'a',
'B': 'b',
'C': 'c',
'D': 'd',
'ITU-R 468': 'm',
'K': 'k'
},
loader = {
url: '',
load: function() {
audioPlayer.src = this.url;
audioPlayer.play();
},
loadLocal: function() {
localAudioElement.click();
},
toggleFullscreen: _ => {
if (document.fullscreenElement === canvas)
document.exitFullscreen();
else
canvas.requestFullscreen();
}
};
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');
const freqDistFolder = settings.addFolder('Frequency distribution');
freqDistFolder.add(visualizerSettings, 'minFreq', 0, 96000).name('Minimum frequency'); // up to 192kHz sample rate
freqDistFolder.add(visualizerSettings, 'maxFreq', 0, 96000).name('Maximum frequency');
freqDistFolder.add(visualizerSettings, 'fscale', fscaleSettings).name('Frequency scale');
freqDistFolder.add(visualizerSettings, 'hzLinearFactor', 0, 100).name('Hz linear factor');
const transformFolder = settings.addFolder('Transform algorithm and window functions');
transformFolder.add(visualizerSettings, 'inputSize', 32, 32768, 1).name('Input size');
transformFolder.add(visualizerSettings, 'fftSize', 32, 32768, 1).name('FFT size');
transformFolder.add(visualizerSettings, 'windowFunction', windowFunctionSettings).name('Window function');
transformFolder.add(visualizerSettings, 'windowParameter', 0, 10).name('Window parameter');
transformFolder.add(visualizerSettings, 'windowSkew', -1, 1).name('Window skew');
transformFolder.add(visualizerSettings, 'useNC').name('Use NC method');
transformFolder.add(visualizerSettings, 'ncDistance', 1, 1024, 1).name('NC method distance');
const amplitudeFolder = settings.addFolder('Amplitude');
amplitudeFolder.add(visualizerSettings, 'useDecibels').name('Use logarithmic amplitude/decibel scale');
amplitudeFolder.add(visualizerSettings, 'useAbsolute').name('Use absolute value');
amplitudeFolder.add(visualizerSettings, 'gamma', 0.5, 10).name('Gamma');
amplitudeFolder.add(visualizerSettings, 'minDecibels', -120, 6).name('Lower amplitude range');
amplitudeFolder.add(visualizerSettings, 'maxDecibels', -120, 6).name('Higher amplitude range');
amplitudeFolder.add(visualizerSettings, 'decoupleAmplitudeFromSpectrum').name('Decouple amplitude scaling of spectrogram from spectrum');
const altAmplitudeFolder = amplitudeFolder.addFolder('Spectrogram colormap scaling');
altAmplitudeFolder.add(visualizerSettings, 'altUseDecibels').name('Use logarithmic amplitude/decibel scale');
altAmplitudeFolder.add(visualizerSettings, 'altUseAbsolute').name('Use absolute value');
altAmplitudeFolder.add(visualizerSettings, 'altGamma', 0.5, 10).name('Gamma');
altAmplitudeFolder.add(visualizerSettings, 'altMinDecibels', -120, 6).name('Lower amplitude range');
altAmplitudeFolder.add(visualizerSettings, 'altMaxDecibels', -120, 6).name('Higher amplitude range');
const weightingFolder = amplitudeFolder.addFolder('Frequency weighting');
weightingFolder.add(visualizerSettings, 'slope', -12, 12).name('Frequency slope (dB per-octave)');
weightingFolder.add(visualizerSettings, 'slopeOffset', 0, 96000).name('Slope offset (Hz = 0dB)');
weightingFolder.add(visualizerSettings, 'equalizeAmount', -12, 12).name('Equalize amount');
weightingFolder.add(visualizerSettings, 'equalizeOffset', 0, 96000).name('Equalize offset');
weightingFolder.add(visualizerSettings, 'equalizeDepth', 0, 96000).name('Equalize depth');
weightingFolder.add(visualizerSettings, 'weightingAmount', -100, 100).name('Weighting amount');
weightingFolder.add(visualizerSettings, 'weightingType', weightingTypes).name('Weighting type');
weightingFolder.add(visualizerSettings, 'slopeFunctionsOffset', 0, 8).name('Slope functions offset (offset by sample rate/FFT size in samples)');
const channelFolder = settings.addFolder('Channel configuration');
channelFolder.add(visualizerSettings, 'channelMode', channelModes).name('Channel mode');
channelFolder.add(visualizerSettings, 'treatAsComplex').name('Treat channel pairs as complex input');
const labelFolder = settings.addFolder('Labels and grid');
labelFolder.add(visualizerSettings, 'showLabels').name('Show horizontal-axis labels');
labelFolder.add(visualizerSettings, 'showLabels2').name('Show horizontal-axis grid');
labelFolder.add(visualizerSettings, 'showLabelsY').name('Show vertical-axis labels');
labelFolder.add(visualizerSettings, 'showLabelsY2').name('Show vertical-axis grid');
labelFolder.add(visualizerSettings, 'amplitudeLabelInterval', 0.5, 48).name('dB label interval');
labelFolder.add(visualizerSettings, 'showDC').name('Show DC label');
labelFolder.add(visualizerSettings, 'showNyquist').name('Show Nyquist frequency label');
labelFolder.add(visualizerSettings, 'showDC2').name('Show DC line');
labelFolder.add(visualizerSettings, 'showNyquist2').name('Show Nyquist frequency line');
labelFolder.add(visualizerSettings, 'mirrorLabels').name('Mirror Y-axis labels');
labelFolder.add(visualizerSettings, 'showBothYLabels').name('Show Y-axis labels on both sides instead of one side only');
labelFolder.add(visualizerSettings, 'alternatingGridPattern').name('Use alternating pattern for Y-axis grid');
labelFolder.add(visualizerSettings, 'spectrogramExtendGrid').name('Extend spectrogram gridlines into screen size');
labelFolder.add(visualizerSettings, 'labelTextAlign', {
'Start': 'start',
'Center': 'center',
'End': 'end'
}).name('Frequency label text alignment');
labelFolder.add(visualizerSettings, 'labelTextBaseline', {
'Alphabetic': 'alphabetic',
'Middle': 'middle',
'Hanging': 'hanging'
}).name('dB label text alignment');
labelFolder.add(visualizerSettings, 'labelTextBaseline2', {
'Alphabetic': 'alphabetic',
'Middle': 'middle',
'Hanging': 'hanging'
}).name('Spectrogram frequency label text alignment');
labelFolder.add(visualizerSettings, 'diffLabels').name('Use difference coloring for labels');
//labelFolder.add(visualizerSettings, 'noteLabels').name('Note labels');
labelFolder.add(visualizerSettings, 'labelMode', labelModes).name('Frequency label mode');
labelFolder.add(visualizerSettings, 'labelMode2', labelModes).name('Frequency grid mode');
labelFolder.add(visualizerSettings, 'labelTuning', 0, 96000).name('Note labels tuning (nearest note = tuning frequency in Hz)');
const appearanceFolder = settings.addFolder('Appearance');
appearanceFolder.add(visualizerSettings, 'display', displayModes).name('Display which').onChange(resizeCanvas);
appearanceFolder.add(visualizerSettings, 'clearSpectrogram').name('Reset spectrogram display');
appearanceFolder.add(visualizerSettings, 'alternateColor').name('Use alternate channel color');
appearanceFolder.add(visualizerSettings, 'useGradient').name('Use color gradient');
appearanceFolder.add(visualizerSettings, 'drawMode', drawModes).name('Draw mode');
appearanceFolder.add(visualizerSettings, 'lineWidth', 0.5, 10).name('Line width');
appearanceFolder.add(visualizerSettings, 'lineJoin', {
'Miter': 'miter',
'Round': 'round',
'Bevel': 'bevel'
}).name('Line join');
appearanceFolder.add(visualizerSettings, 'miterLimit', 1, 100).name('Line miter limit');
appearanceFolder.add(visualizerSettings, 'lowDetail').name('Low detail mode');
appearanceFolder.add(visualizerSettings, 'useBars').name('Draw bars instead of lines');
appearanceFolder.add(visualizerSettings, 'barSpacing', 0, 1024).name('Bar spacing');
appearanceFolder.add(visualizerSettings, 'showStrokeRectAsBars').name('Show stroke rect as stroke bars instead of cap');
appearanceFolder.add(visualizerSettings, 'darkMode').name('Dark mode');
settings.add(visualizerSettings, 'freeze').name('Freeze analyser');
settings.add(visualizerSettings, 'compensateDelay').name('Delay compensation');
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;
auxCanvas.width = canvas.width;
auxCanvas.height = visualizerSettings.display === 'both' ? Math.trunc(canvas.height/2) : canvas.height;
staticSpectrogramIdx = 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);
}
const test = map(0, 0, 1, -1, 1); // Smoke testing
visualize();
function visualize() {
delay.delayTime.value = visualizerSettings.inputSize/audioCtx.sampleRate * visualizerSettings.compensateDelay;
// Visualization part
if (!visualizerSettings.freeze) {
analyser.getFloatTimeDomainData(dataArray);
if (visualizerSettings.mode !== 'mono') {
analyserL.getFloatTimeDomainData(dataArrayL);
analyserR.getFloatTimeDomainData(dataArrayR);
}
}
const fftData = new Array(visualizerSettings.fftSize).fill(0),
fftData1 = Array.from(fftData),
fftData2 = Array.from(fftData),
fftData3 = Array.from(fftData),
fftData4 = Array.from(fftData);
let norm = 0,
spectrum0,
spectrum1,
spectrum2,
spectrum3,
spectrum4;
for (let i = 0; i < visualizerSettings.inputSize; i++) {
const x = map(i, 0, visualizerSettings.inputSize, -1, 1),
w = applyWindow(x, visualizerSettings.windowFunction, visualizerSettings.windowParameter, true, visualizerSettings.windowSkew),
magnitude = dataArray[i+analyser.fftSize-visualizerSettings.inputSize],
l = dataArrayL[i+analyserL.fftSize-visualizerSettings.inputSize],
r = dataArrayR[i+analyserR.fftSize-visualizerSettings.inputSize],
m = (l+r)/2,
s = (l-r)/2;
norm += w;
fftData[idxWrapOver(i, fftData.length)] += magnitude * w;
fftData1[idxWrapOver(i, fftData1.length)] += l * w;
fftData2[idxWrapOver(i, fftData2.length)] += r * w;
fftData3[idxWrapOver(i, fftData3.length)] += m * w;
fftData4[idxWrapOver(i, fftData4.length)] += s * w;
}
const isMono = visualizerSettings.channelMode !== 'stereo' && visualizerSettings.channelMode !== 'ms' && visualizerSettings.channelMode !== 'both',
bgColor = visualizerSettings.darkMode ? (!visualizerSettings.alternateColor && isMono ? '#202020' : '#000') : '#fff',
fgColor = visualizerSettings.darkMode ? (!visualizerSettings.alternateColor && isMono ? '#c0c0c0' : '#fff') : '#000',
cL = 'rgb(79, 129, 189)',
cR = 'rgb(192, 80, 77)',
cM = 'rgb(155, 187, 87)',
cS = 'rgb(128, 100, 162)',
isSpectrogramOnly = visualizerSettings.display === 'spectrogram' || visualizerSettings.display === 'static',
isSpectrogram = visualizerSettings.display === 'spectrogram' || visualizerSettings.display === 'both' || visualizerSettings.display === 'static',
isSpectrumandSpectrogram = visualizerSettings.display === 'both',
ncDistance = visualizerSettings.ncDistance,
useNC = visualizerSettings.useNC,
altAmplitude = visualizerSettings.decoupleAmplitudeFromSpectrum;
auxCtx.imageSmoothingEnabled = false;
ctx.globalCompositeOperation = 'source-over';
ctx.fillStyle = bgColor;
ctx.strokeStyle = bgColor;
ctx.fillRect(0, 0, canvas.width, canvas.height);
ctx.lineWidth = visualizerSettings.lineWidth;
ctx.lineJoin = visualizerSettings.lineJoin;
ctx.miterLimit = visualizerSettings.miterLimit;
switch(visualizerSettings.channelMode) {
case 'stereo':
case 'ms':
case 'both':
const isAlternate = visualizerSettings.alternateColor,
color1 = isAlternate ? cM : cL,
color2 = isAlternate ? cS : cR,
color3 = visualizerSettings.channelMode === 'ms' ? color1 : isAlternate ? cL : cM,
color4 = visualizerSettings.channelMode === 'ms' ? color2 : isAlternate ? cR : cS,
isComplex = visualizerSettings.treatAsComplex;
ctx.globalCompositeOperation = visualizerSettings.darkMode ? 'lighten': 'darken';
if (visualizerSettings.channelMode === 'stereo' || visualizerSettings.channelMode === 'both') {
let value1 = fftData1.map(x => x*fftData1.length/norm*Math.SQRT2),
value2 = fftData2.map(x => x*fftData2.length/norm*Math.SQRT2);
if (isComplex) {
const complexSpectrum = calcComplexInputFFT(value1, value2),
ncSpectrum = useNC ? ncMethod(complexSpectrum, ncDistance) : [];
spectrum1 = new Array(complexSpectrum.length);
spectrum2 = new Array(complexSpectrum.length);
for (let i = 0; i < complexSpectrum.length; i++) {
const j = complexSpectrum.length-i;
spectrum1[i] = useNC ? ncSpectrum[idxWrapOver(i, ncSpectrum.length)] : complexSpectrum[idxWrapOver(i, complexSpectrum.length)].magnitude;
spectrum2[i] = useNC ? ncSpectrum[idxWrapOver(j, ncSpectrum.length)] : complexSpectrum[idxWrapOver(j, complexSpectrum.length)].magnitude;
}
}
else {
if (useNC) {
const temp1 = calcComplexFFT(value1),
temp2 = calcComplexFFT(value2);
spectrum1 = ncMethod(temp1, ncDistance);
spectrum2 = ncMethod(temp2, ncDistance);
}
else {
spectrum1 = calcFFT(value1, true),
spectrum2 = calcFFT(value2, true);
}
}
ctx.fillStyle = color1;
ctx.strokeStyle = color1;
if (!isSpectrogramOnly)
drawSpectrum(spectrum1, fftData1.length, isSpectrumandSpectrogram);
ctx.fillStyle = color2;
ctx.strokeStyle = color2;
if (!isSpectrogramOnly)
drawSpectrum(spectrum2, fftData2.length, isSpectrumandSpectrogram);
}
if (visualizerSettings.channelMode === 'ms' || visualizerSettings.channelMode === 'both') {
let value3 = fftData3.map(x => x*fftData3.length/norm*Math.SQRT2),
value4 = fftData4.map(x => x*fftData4.length/norm*Math.SQRT2);
if (isComplex) {
const complexSpectrum = calcComplexInputFFT(value3, value4),
ncSpectrum = useNC ? ncMethod(complexSpectrum, ncDistance) : [];
spectrum3 = new Array(complexSpectrum.length);
spectrum4 = new Array(complexSpectrum.length);
for (let i = 0; i < complexSpectrum.length; i++) {
const j = complexSpectrum.length-i;
spectrum3[i] = useNC ? ncSpectrum[idxWrapOver(i, ncSpectrum.length)] : complexSpectrum[idxWrapOver(i, complexSpectrum.length)].magnitude;
spectrum4[i] = useNC ? ncSpectrum[idxWrapOver(j, ncSpectrum.length)] : complexSpectrum[idxWrapOver(j, complexSpectrum.length)].magnitude;
}
}
else {
if (useNC) {
const temp1 = calcComplexFFT(value3),
temp2 = calcComplexFFT(value4);
spectrum3 = ncMethod(temp1, ncDistance);
spectrum4 = ncMethod(temp2, ncDistance);
}
else {
spectrum3 = calcFFT(value3, true),
spectrum4 = calcFFT(value4, true);
}
}
ctx.fillStyle = color3;
ctx.strokeStyle = color3;
if (!isSpectrogramOnly)
drawSpectrum(spectrum3, fftData1.length, isSpectrumandSpectrogram);
ctx.fillStyle = color4;
ctx.strokeStyle = color4;
if (!isSpectrogramOnly)
drawSpectrum(spectrum4, fftData2.length, isSpectrumandSpectrogram);
}
break;
default:
if (useNC)
spectrum0 = ncMethod(calcComplexFFT(fftData.map(x => x*fftData.length/norm*Math.SQRT2)), ncDistance);
else
spectrum0 = calcFFT(fftData.map(x => x*fftData.length/norm*Math.SQRT2), true);
if (visualizerSettings.useGradient) {
const grad = ctx.createLinearGradient(0, 0, 0, canvas.height);
grad.addColorStop(0, visualizerSettings.darkMode ? (visualizerSettings.alternateColor ? 'rgb(0, 128, 255)' : '#569cd6'): (visualizerSettings.alternateColor ? '#008' : 'rgb(0, 102, 204)'));
grad.addColorStop(1/(1+isSpectrumandSpectrogram), visualizerSettings.darkMode ? (visualizerSettings.alternateColor ? '#fff' : '#c0c0c0') : '#000');
ctx.fillStyle = grad;
ctx.strokeStyle = grad;
}
else {
ctx.fillStyle = fgColor;
ctx.strokeStyle = fgColor;
}
if (!isSpectrogramOnly)
drawSpectrum(spectrum0, fftData.length, isSpectrumandSpectrogram);
}
if (isSpectrogram) {
ctx.globalCompositeOperation = 'source-over';
const spectrogramBars = generateBarData(isSpectrumandSpectrogram ? auxCanvas.width : auxCanvas.height, fftData.length, audioCtx.sampleRate);
for (let i = 0; i < spectrogramBars.length; i++) {
let value = 0,
value1 = 0,
value2 = 0,
value3 = 0,
value4 = 0;
for (let idx = spectrogramBars[i].lo; idx <= spectrogramBars[i].hi; idx++) {
const binIdx = idxWrapOver(idx, fftData.length);
if (spectrum0 !== undefined)
value = Math.max(value, spectrum0[binIdx]*weightSpectrumAtFreq(fftBinToHertz(idx + visualizerSettings.slopeFunctionsOffset, spectrum0.length, audioCtx.sampleRate)));
if (spectrum1 !== undefined)
value1 = Math.max(value1, spectrum1[binIdx]*weightSpectrumAtFreq(fftBinToHertz(idx + visualizerSettings.slopeFunctionsOffset, spectrum1.length, audioCtx.sampleRate)));
if (spectrum2 !== undefined)
value2 = Math.max(value2, spectrum2[binIdx]*weightSpectrumAtFreq(fftBinToHertz(idx + visualizerSettings.slopeFunctionsOffset, spectrum2.length, audioCtx.sampleRate)));
if (spectrum3 !== undefined)
value3 = Math.max(value3, spectrum3[binIdx]*weightSpectrumAtFreq(fftBinToHertz(idx + visualizerSettings.slopeFunctionsOffset, spectrum3.length, audioCtx.sampleRate)));
if (spectrum4 !== undefined)
value4 = Math.max(value4, spectrum4[binIdx]*weightSpectrumAtFreq(fftBinToHertz(idx + visualizerSettings.slopeFunctionsOffset, spectrum4.length, audioCtx.sampleRate)));
}
let color;
const darkMode = visualizerSettings.darkMode;
switch(visualizerSettings.channelMode) {
case 'stereo':
case 'ms':
case 'both':
const mag1 = spectrum1 !== undefined ? ascale(value1, altAmplitude) : 0,
mag2 = spectrum2 !== undefined ? ascale(value2, altAmplitude) : 0,
mag3 = spectrum3 !== undefined ? ascale(value3, altAmplitude) : 0,
mag4 = spectrum4 !== undefined ? ascale(value4, altAmplitude) : 0,
sign = visualizerSettings.darkMode * 2 - 1,
isMSOnly = visualizerSettings.channelMode === 'ms',
isAlternate = visualizerSettings.alternateColor,
compliment1 = (isMSOnly && !isAlternate) || (!isMSOnly && isAlternate) ? mag3 : mag1,
compliment2 = (isMSOnly && !isAlternate) || (!isMSOnly && isAlternate) ? mag4 : mag2,
compliment3 = (isMSOnly && !isAlternate) || (!isMSOnly && isAlternate) ? mag1 : mag3,
compliment4 = (isMSOnly && !isAlternate) || (!isMSOnly && isAlternate) ? mag2 : mag4,
mathFunc = darkMode ? 'max' : 'min',
colors = [
{
r: 79,
g: 129,
b: 189
},
{
r: 192,
g: 80,
b: 77
},
{
r: 155,
g: 187,
b: 67
},
{
r: 128,
g: 100,
b: 162
}
],
background = 255 * (!darkMode),
colorFunc = (x, y) => map(x, 0, 1, background, y);
color = calcRGB(
Math[mathFunc](background, colorFunc(compliment1, colors[0].r), colorFunc(compliment2, colors[1].r), colorFunc(compliment3, colors[2].r), colorFunc(compliment4, colors[3].r) ),
Math[mathFunc](background, colorFunc(compliment1, colors[0].g), colorFunc(compliment2, colors[1].g), colorFunc(compliment3, colors[2].g), colorFunc(compliment4, colors[3].g) ),
Math[mathFunc](background, colorFunc(compliment1, colors[0].b), colorFunc(compliment2, colors[1].b), colorFunc(compliment3, colors[2].b), colorFunc(compliment4, colors[3].b) )
);
break;
default:
const mag = ascale(value, altAmplitude),
bg = 32 * (!visualizerSettings.alternateColor && darkMode);
if (visualizerSettings.useGradient) {
const colors = [
// foobar2000 color scheme
{
r: visualizerSettings.alternateColor ? 0 : 0,
g: visualizerSettings.alternateColor ? 0 : 102,
b: visualizerSettings.alternateColor ? 136 : 204
},
// for dark mode in DUI
{
r: visualizerSettings.alternateColor ? 0 : 86,
g: visualizerSettings.alternateColor ? 128 : 156,
b: visualizerSettings.alternateColor ? 255 : 214
}
],
foreground = (visualizerSettings.alternateColor ? 255 : 192) * darkMode,
halfway = mag > 0.5;
color = calcRGB(
map(mag, halfway/2, halfway/2+0.5, halfway ? colors[darkMode*1].r + bg : 255*(!darkMode) + bg, halfway ? foreground : colors[darkMode*1].r + bg),
map(mag, halfway/2, halfway/2+0.5, halfway ? colors[darkMode*1].g + bg : 255*(!darkMode) + bg, halfway ? foreground : colors[darkMode*1].g + bg),
map(mag, halfway/2, halfway/2+0.5, halfway ? colors[darkMode*1].b + bg : 255*(!darkMode) + bg, halfway ? foreground : colors[darkMode*1].b + bg)
);
}
else
color = calcRGB(mag*255*(darkMode*2-1) + 255 * (!darkMode) + bg, mag*255*(darkMode*2-1) + 255 * (!darkMode) + bg, mag*255*(darkMode*2-1) + 255 * (!darkMode) + bg);
}
const r = color.r,
g = color.g,
b = color.b,
segmentStart = isNaN(spectrogramBars[i].start) ? 0 : clamp(spectrogramBars[i].start, 0, isSpectrumandSpectrogram ? auxCanvas.width : auxCanvas.height),
segmentEnd = isNaN(spectrogramBars[i].end) ? 0 : clamp(spectrogramBars[i].end, 0, isSpectrumandSpectrogram ? auxCanvas.width : auxCanvas.height),
pos = segmentStart,
delta = segmentEnd - segmentStart;
auxCtx.fillStyle = `rgb(${r}, ${g}, ${b})`;
auxCtx.fillRect(pos * isSpectrumandSpectrogram + (visualizerSettings.display === 'static' ? staticSpectrogramIdx : (auxCanvas.width-1)) * isSpectrogramOnly, (auxCanvas.height - pos) * isSpectrogramOnly, delta * isSpectrumandSpectrogram + 1 * isSpectrogramOnly, -delta * isSpectrogramOnly + 1 * isSpectrumandSpectrogram);
}
if (auxCanvas.width > 0 && auxCanvas.height > 0)
auxCtx.drawImage(auxCanvas, -1 * isSpectrogramOnly * (visualizerSettings.display !== 'static'), 1 * isSpectrumandSpectrogram);
ctx.fillStyle = bgColor;
ctx.fillRect(canvas.width-auxCanvas.width, canvas.height-auxCanvas.height, auxCanvas.width, auxCanvas.height);
if (auxCanvas.width > 0 && auxCanvas.height > 0)
ctx.drawImage(auxCanvas, 0, canvas.height-auxCanvas.height);
if (visualizerSettings.display === 'static')
staticSpectrogramIdx = idxWrapOver(staticSpectrogramIdx+1, auxCanvas.width);
}
ctx.globalCompositeOperation = visualizerSettings.diffLabels ? 'difference' : 'source-over';
// label part
ctx.lineWidth = 1;
ctx.lineJoin = 'miter';
ctx.miterLimit = 10;
ctx.fillStyle = visualizerSettings.diffLabels ? '#fff' : fgColor;
ctx.strokeStyle = visualizerSettings.diffLabels ? '#fff' : fgColor;
ctx.font = `${Math.trunc(10*devicePixelRatio)}px sans-serif`;
ctx.textAlign = visualizerSettings.labelTextAlign //isSpectrumandSpectrogram ? 'center' : 'start';
ctx.textBaseline = isSpectrogram ? visualizerSettings.labelTextBaseline2 : 'alphabetic' //isSpectrumandSpectrogram ? 'middle' : 'alphabetic';
// Frequency label part
if (visualizerSettings.showLabels || visualizerSettings.showDC || visualizerSettings.showNyquist || visualizerSettings.showLabels ||
visualizerSettings.showLabels2 || visualizerSettings.showDC2 || visualizerSettings.showNyquist2 || visualizerSettings.showLabels2) {
ctx.globalAlpha = 0.5;
ctx.setLineDash([]);
const freqLabels = getFreqGridTable(visualizerSettings.showLabels, visualizerSettings.labelMode, visualizerSettings.showDC, visualizerSettings.showNyquist),
freqLines = getFreqGridTable(visualizerSettings.showLabels2, visualizerSettings.labelMode2, visualizerSettings.showDC2, visualizerSettings.showNyquist2),
notes = ['C', 'C#', 'D', 'D#', 'E', 'F', 'F#', 'G', 'G#', 'A', 'A#', 'B'],
isNote = visualizerSettings.labelMode === 'note',
isNote2 = visualizerSettings.labelMode2 === 'note';
freqLabels.map(x => {
const note = isFinite(Math.log2(x)) ? notes[idxWrapOver(Math.round(Math.log2(x)*12), notes.length)] : 'DC',
isSharp = note.includes('#'),
isC = note === 'C',
isFirstFreq = x === 0,
isLastFreq = x === audioCtx.sampleRate/2 && visualizerSettings.showNyquist;
const label = isLastFreq ? 'Nyquist' : isNote || isFirstFreq ? `${note}${isC ? Math.trunc(Math.log2(x)-4) : ''}` : (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), canvas.height * isSpectrogramOnly, canvas.width * (!isSpectrogramOnly));
ctx.globalAlpha = 1;
if (isSpectrogramOnly)
ctx.textAlign = visualizerSettings.mirrorLabels ? 'end' : 'start';
ctx.fillText(label, posX * (!isSpectrogramOnly) + isSpectrogramOnly * canvas.width * visualizerSettings.mirrorLabels, isSpectrogramOnly ? posX : canvas.height / (1+isSpectrumandSpectrogram));
if (visualizerSettings.showBothYLabels && isSpectrogramOnly) {
ctx.textAlign = !visualizerSettings.mirrorLabels ? 'end' : 'start';
ctx.fillText(label, canvas.width * (!visualizerSettings.mirrorLabels), posX);
}
});
freqLines.map(x => {
const note = isFinite(Math.log2(x)) ? notes[idxWrapOver(Math.round(Math.log2(x)*12), notes.length)] : 'DC',
isSharp = note.includes('#'),
isC = note === 'C',
isFirstFreq = x === 0,
isLastFreq = x === audioCtx.sampleRate/2 && visualizerSettings.showNyquist2;
ctx.globalAlpha = isLastFreq || isFirstFreq ? 1 : isNote2 ? (isSharp ? 0.2 : isC ? 0.8 : 0.5) : 0.5;
const 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), canvas.height * isSpectrogramOnly, canvas.width * (!isSpectrogramOnly)),
lineWidth = 10*devicePixelRatio*ctx.globalAlpha;
ctx.globalAlpha = (isSpectrogramOnly ? !visualizerSettings.spectrogramExtendGrid : false) ? 1 : ctx.globalAlpha;
ctx.beginPath();
ctx.lineTo(isSpectrogramOnly ? visualizerSettings.spectrogramExtendGrid ? 0 : canvas.width * visualizerSettings.mirrorLabels : posX, isSpectrogramOnly ? posX : canvas.height/(1+isSpectrumandSpectrogram));
ctx.lineTo(isSpectrogramOnly ? visualizerSettings.spectrogramExtendGrid ? canvas.width : canvas.width * visualizerSettings.mirrorLabels + lineWidth * (1-visualizerSettings.mirrorLabels*2) : posX, isSpectrogramOnly ? posX : 0);
ctx.stroke();
if (visualizerSettings.showBothYLabels && isSpectrogramOnly && !visualizerSettings.spectrogramExtendGrid) {
ctx.beginPath();
ctx.lineTo(canvas.width * (!visualizerSettings.mirrorLabels), posX);
ctx.lineTo(canvas.width * (!visualizerSettings.mirrorLabels) + lineWidth * (1-(!visualizerSettings.mirrorLabels)*2), posX);
ctx.stroke();
}
});
ctx.setLineDash([]);
ctx.globalAlpha = 1;
ctx.textAlign = 'start';
ctx.textBaseline = 'alphabetic';
}
// Amplitude/decibel label part
if ((visualizerSettings.showLabelsY || visualizerSettings.showLabelsY2) && !isSpectrogramOnly) {
const dBLabelData = [-Infinity],
mindB = Math.min(visualizerSettings.minDecibels, visualizerSettings.maxDecibels),
maxdB = Math.max(visualizerSettings.minDecibels, visualizerSettings.maxDecibels),
minLabelIdx = Math.round(mindB/visualizerSettings.amplitudeLabelInterval),
maxLabelIdx = Math.round(maxdB/visualizerSettings.amplitudeLabelInterval);
if (isFinite(minLabelIdx) && isFinite(maxLabelIdx)) {
for (let i = maxLabelIdx; i >= minLabelIdx; i--) {
dBLabelData.push({
data: i*visualizerSettings.amplitudeLabelInterval,
pattern: idxWrapOver(i, 2)
});
}
}
ctx.globalAlpha = 0.5;
ctx.setLineDash([]);
dBLabelData.map(i => {
const x = i.data,
label = `${x}dB`,
posY = map(ascale(10 ** (x/20)), 0, 1, canvas.height/(1+isSpectrumandSpectrogram), 0);
ctx.textBaseline = visualizerSettings.labelTextBaseline;
if (posY <= canvas.height/2 || !isSpectrumandSpectrogram) {
if (visualizerSettings.showLabelsY2) {
ctx.globalAlpha = 0.5;
if (visualizerSettings.alternatingGridPattern) {
if (i.pattern)
ctx.setLineDash([4,4]);
else
ctx.setLineDash([]);
}
ctx.beginPath();
ctx.lineTo(0, posY);
ctx.lineTo(canvas.width, posY);
ctx.stroke();
}
if (visualizerSettings.showLabelsY) {
ctx.globalAlpha = 1;
ctx.textAlign = visualizerSettings.mirrorLabels ? 'end' : 'start';
ctx.fillText(label, canvas.width * visualizerSettings.mirrorLabels, posY);
if (visualizerSettings.showBothYLabels) {
ctx.textAlign = !visualizerSettings.mirrorLabels ? 'end' : 'start';
ctx.fillText(label, canvas.width * (!visualizerSettings.mirrorLabels), posY);
}
}
}
});
ctx.setLineDash([]);
ctx.globalAlpha = 1;
ctx.textAlign = 'start';
ctx.textBaseline = 'alphabetic';
}
requestAnimationFrame(visualize);
}
function generateBarData(size = 1920, length = 4800, sampleRate = 48000) {
const isReversed = visualizerSettings.minFreq > visualizerSettings.maxFreq,
minRange = hertzToFFTBin(visualizerSettings.minFreq, isReversed ? 'ceil' : 'floor', length, sampleRate),
maxRange = hertzToFFTBin(visualizerSettings.maxFreq, isReversed ? 'floor' : 'ceil', length, sampleRate),
spectrogramBars = [];
for (let i = Math.min(minRange, maxRange); i <= Math.max(minRange, maxRange); i++) {
const lowerBound = map(fscale(fftBinToHertz(i-0.5, length, sampleRate), visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.minFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.maxFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), 0, 1),
higherBound = map(fscale(fftBinToHertz(i+0.5, length, sampleRate), visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.minFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), fscale(visualizerSettings.maxFreq, visualizerSettings.fscale, visualizerSettings.hzLinearFactor/100), 0, 1),
lowerVisible = clamp(Math.round(lowerBound * size), 0, size),
higherVisible = clamp(Math.round(higherBound * size), 0, size);
if (lowerVisible !== higherVisible) {
spectrogramBars.push({
lo: i,
hi: i,
start: lowerVisible,
end: higherVisible
});
}
else if (spectrogramBars.length > 0) {
const lastBin = spectrogramBars[spectrogramBars.length-1];
lastBin.lo = Math.min(lastBin.lo, i);
lastBin.hi = Math.max(lastBin.hi, i);
}
}
return spectrogramBars;
}
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 'cosh 2':
case 'hyperbolic cosine 2':
return Math.E ** (-(Math.cosh(x*windowParameter)-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)) ** windowParameter;
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);
case 'galss':
return (((1-1/(x+2))*(1-1/(-x+2)))*4) ** 2 * -(Math.tanh(Math.SQRT2*(-x+1))*Math.tanh(Math.SQRT2*(-x-1)))/(Math.tanh(Math.SQRT2) ** 2);
case 'glizzy':
return (Math.cos(x*Math.PI/2) ** 2) * (
0.5 +
Math.cos(x*Math.PI) * 0.853553390593 +
Math.cos(x*Math.PI*2) * 0.5 +
Math.cos(x*Math.PI*3) * 0.146446609407
) / 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 'cam':
case 'cams':
return Math.log2((x/1000+0.312)/(x/1000+14.675));
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))));
case 'adjustable bark':
return (26.81 * x)/((10 ** (freqSkew*4)) + x);
case 'period':
return 1/x;
}
}
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 'cam':
case 'cams':
return (14.675 * (2 ** x) - 0.312)/(1-(2 ** x)) * 1000;
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));
case 'adjustable bark':
return (10 ** (freqSkew*4)) / (26.81 / x - 1);
case 'period':
return 1/x;
}
}
function ascale(x, alt = false) {
const minDecibels = alt ? visualizerSettings.altMinDecibels : visualizerSettings.minDecibels,
maxDecibels = alt ? visualizerSettings.altMaxDecibels : visualizerSettings.maxDecibels,
useAbsolute = alt ? visualizerSettings.altUseAbsolute : visualizerSettings.useAbsolute,
gamma = alt ? visualizerSettings.altGamma : visualizerSettings.gamma,
useDecibels = alt ? visualizerSettings.altUseDecibels : visualizerSettings.useDecibels;
if (useDecibels)
return map(20*Math.log10(x), minDecibels, maxDecibels, 0, 1);
else
return map(x ** (1/gamma), !useAbsolute * (10 ** (minDecibels/20)) ** (1/gamma), (10 ** (maxDecibels/20)) ** (1/gamma), 0, 1);
}
// needed for note labels and grids
function generateOctaveBands(bandsPerOctave = 12, lowerNote = 4, higherNote = 123, detune = 0, tuningFreq = 440, bandwidth = 0.5) {
const tuningNote = isFinite(Math.log2(tuningFreq)) ? Math.round((Math.log2(tuningFreq)-4)*12)*2 : 0,
root24 = 2 ** ( 1 / 24 ),
c0 = tuningFreq * root24 ** -tuningNote, // ~16.35 Hz
groupNotes = 24/bandsPerOctave;
let bands = [];
for (let i = Math.round(lowerNote*2/groupNotes); i <= Math.round(higherNote*2/groupNotes); i++) {
bands.push({
lo: c0 * root24 ** ((i-bandwidth)*groupNotes+detune),
ctr: c0 * root24 ** (i*groupNotes+detune),
hi: c0 * root24 ** ((i+bandwidth)*groupNotes+detune)
});
}
return bands;
}
function drawSpectrum(spectrum, length, half = false) {
// Spectrum (FFT) visualization part
const isFill = visualizerSettings.drawMode === 'fill' || visualizerSettings.drawMode === 'both',
isStroke = visualizerSettings.drawMode === 'stroke' || visualizerSettings.drawMode === 'both',
isCap = isStroke && !visualizerSettings.showStrokeRectAsBars,
isFlipped = visualizerSettings.minFreq > visualizerSettings.maxFreq,
minIdx = hertzToFFTBin(visualizerSettings.minFreq, isFlipped ? 'ceil' : 'floor', length, audioCtx.sampleRate),
maxIdx = hertzToFFTBin(visualizerSettings.maxFreq, isFlipped ? 'floor' : 'ceil', length, audioCtx.sampleRate);
if (visualizerSettings.useBars) {
const spectrogramBars = generateBarData(canvas.width, length, audioCtx.sampleRate);
for (let i = 0; i < spectrogramBars.length; i++) {
const segmentStart = isNaN(spectrogramBars[i].start) ? 0 : spectrogramBars[i].start,
segmentEnd = isNaN(spectrogramBars[i].end) ? 0 : spectrogramBars[i].end,
x = segmentStart,
y = canvas.height/(1+half),
delta = segmentEnd - segmentStart,
w = Math[delta < 0 ? 'min' : 'max'](Math.sign(delta), delta-Math.sign(delta)*visualizerSettings.barSpacing);
if (isCap)
ctx.beginPath();
let mag = 0;
for (let j = spectrogramBars[i].lo; j <= spectrogramBars[i].hi; j++) {
const amp = spectrum[idxWrapOver(j, spectrum.length)]*weightSpectrumAtFreq(fftBinToHertz(j + visualizerSettings.slopeFunctionsOffset, spectrum.length, audioCtx.sampleRate));
mag = Math.max(mag, amp);
if (isCap && !visualizerSettings.lowDetail)
ctx.rect(x, (canvas.height-ascale(amp)*canvas.height)/(1+half), w, ctx.lineWidth);
}
const h = -ascale(mag)*canvas.height/(1+half);
if (isCap && visualizerSettings.lowDetail)
ctx.rect(x, (canvas.height-ascale(mag)*canvas.height)/(1+half), w, ctx.lineWidth)
ctx.globalAlpha = visualizerSettings.drawMode === 'both' ? 0.5 : 1;
if (isFill)
ctx.fillRect(x, y, w, h);
ctx.globalAlpha = 1;
if (isCap)
ctx.fill();
else if (isStroke)
ctx.strokeRect(x, y, w, h);
}
}
else {
let deltaX,
y = 0,
backToBack = true;
ctx.beginPath();
if (isFill) {
ctx.lineTo(canvas.width * isFlipped, canvas.height);
}
ctx.lineTo(canvas.width * isFlipped, map(ascale(spectrum[idxWrapOver(minIdx, spectrum.length)]*weightSpectrumAtFreq(fftBinToHertz(minIdx + visualizerSettings.slopeFunctionsOffset, spectrum.length, audioCtx.sampleRate))), 0, 1, canvas.height / (1+half), 0));
for (let i = Math.min(minIdx, maxIdx); i < Math.max(minIdx, maxIdx); i++) {
const x = map(fscale(fftBinToHertz(i, 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),
amp = spectrum[idxWrapOver(i, spectrum.length)]*weightSpectrumAtFreq(fftBinToHertz(i + visualizerSettings.slopeFunctionsOffset, spectrum.length, audioCtx.sampleRate));
if ((Math.round(x) - Math.round(deltaX) !== 0) || !visualizerSettings.lowDetail) {
if (backToBack || !visualizerSettings.lowDetail)
y = amp;
ctx.lineTo(x, map(ascale(y), 0, 1, canvas.height / (1+half), 0));
backToBack = true;
y = 0;
}
else {
backToBack = false;
y = Math.max(y, amp);
}
deltaX = x;
}
ctx.lineTo(canvas.width * (1-isFlipped), map(ascale(spectrum[idxWrapOver(maxIdx, spectrum.length)]*weightSpectrumAtFreq(fftBinToHertz(maxIdx + visualizerSettings.slopeFunctionsOffset, spectrum.length, audioCtx.sampleRate))), 0, 1, canvas.height / (1+half), 0));
if (isFill) {
ctx.lineTo(canvas.width * (1-isFlipped), canvas.height)
}
ctx.globalAlpha = visualizerSettings.drawMode === 'both' ? 0.5 : 1;
if (isFill)
ctx.fill();
ctx.globalAlpha = 1;
if (isStroke)
ctx.stroke();
}
}
function calcRGB(r = 0, g = 0, b = 0) {
return {
r: isNaN(r) ? 0 : clamp(r, 0, 255),
g: isNaN(g) ? 0 : clamp(g, 0, 255),
b: isNaN(b) ? 0 : clamp(b, 0, 255)
};
}
// Weighting and frequency slope functions
function calcFreqTilt(x, amount = 3, offset = 1000) {
return (x/offset) ** (amount/6);
}
function applyEqualize(x, amount = 6, depth = 1024, offset = 44100) {
const pos = x * depth / offset,
bias = 1.0025 ** (-pos) * 0.04;
return (10 * Math.log10(1 + bias + (pos + 1) * (9 - bias)/depth)) ** (amount/6);
}
function applyWeight(x, weightAmount = 1, weightType = 'a') {
const f2 = x ** 2;
switch (weightType) {
case 'a':
return (1.2588966 * 148840000 * (f2 ** 2) /
((f2 + 424.36) * Math.sqrt((f2 + 11599.29) * (f2 + 544496.41)) * (f2 + 148840000))) ** weightAmount;
case 'b':
return (1.019764760044717 * 148840000 * (x ** 3) /
((f2 + 424.36) * Math.sqrt(f2 + 25122.25) * (f2 + 148840000))) ** weightAmount;
case 'c':
return (1.0069316688518042 * 148840000 * f2 /
((f2 + 424.36) * (f2 + 148840000))) ** weightAmount;
case 'd':
return ((x / 6.8966888496476e-5) * Math.sqrt(
(
((1037918.48 - f2)*(1037918.48 - f2) + 1080768.16*f2) /
((9837328 - f2)*(9837328 - f2) + 11723776*f2)
) / ((f2 + 79919.29) * (f2 + 1345600))
)) ** weightAmount;
case 'm':
const h1 = -4.737338981378384e-24*(f2 ** 3) + 2.043828333606125e-15*(f2 ** 2) - 1.363894795463638e-7*f2 + 1,
h2 = 1.306612257412824e-19*(x ** 5) - 2.118150887518656e-11*(x ** 3) + 5.559488023498642e-4*x;
return (8.128305161640991 * 1.246332637532143e-4 * x / Math.hypot(h1, h2)) ** weightAmount;
case 'k':
const c2 = 4284900, // from 2070
z2 = 1690000, // from 1300
f = 80,
s = Math.sqrt((1 + (f2) / z2) / (1 + (f2) / c2)), // shelving part
l = ((x/f) ** 2)/Math.sqrt(0.5*(1 - (x/f) ** 2) ** 2 + (x/f) ** 2) / Math.SQRT2; // lowpass part
return (s*l) ** weightAmount;
default:
return 1;
}
}
function weightSpectrumAtFreq(x) {
return calcFreqTilt(x, visualizerSettings.slope, visualizerSettings.slopeOffset) * applyEqualize(x, visualizerSettings.equalizeAmount, visualizerSettings.equalizeDepth, visualizerSettings.equalizeOffset) * applyWeight(x, visualizerSettings.weightingAmount/100, visualizerSettings.weightingType)
}
// NC method
function ncMethod(fftData, distance = 1) {
const magnitudeData = [],
offset = Math.trunc(distance/2);
for (let i = 0; i < fftData.length; i++) {
const cosL = fftData[idxWrapOver(i-offset, fftData.length)].re,
sinL = fftData[idxWrapOver(i-offset, fftData.length)].im,
cosR = fftData[idxWrapOver(i-offset+distance, fftData.length)].re,
sinR = fftData[idxWrapOver(i-offset+distance, fftData.length)].im;
magnitudeData[i] = Math.sqrt(Math.max(0, -(cosL*cosR)-(sinL*sinR)));
}
return magnitudeData;
}
function getFreqGridTable(showLabels, labelMode, showDC, showNyquist) {
const freqLabels = [];
let freqsTable;
switch(labelMode) {
case 'decade':
freqsTable = [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];
break;
case 'decade 2':
freqsTable = [10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000];
break;
case 'decade 3':
freqsTable = [10, 100, 1000, 10000];
break;
case 'octave':
freqsTable = [31, 63.5, 125, 250, 500, 1000, 2000, 4000, 8000, 16000];
break;
case 'powers of two':
freqsTable = [32, 64, 128, 256, 512, 1024, 2048, 4096, 8192, 16384];
break;
case 'note':
freqsTable = generateOctaveBands(12, 0, 132, 0, visualizerSettings.labelTuning).map(x => x.ctr);
break;
case 'bark':
freqsTable = [50, 150, 250, 350, 450, 570, 700, 840, 1000, 1170, 1370, 1600, 1850, 2150, 2500, 2900, 3400, 4000, 4800, 5800, 7000, 8500, 10500, 13500];
break;
case 'linear':
freqsTable = [1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 11000, 12000, 13000, 14000, 15000, 16000, 17000, 18000, 19000, 20000];
}
if (showLabels)
freqLabels.push(...freqsTable);
if (showDC)
freqLabels.push(0);
if (showNyquist)
freqLabels.push(audioCtx.sampleRate/2);
return freqLabels;
}
Also see: Tab Triggers