mirror of
https://github.com/scratchfoundation/paper.js.git
synced 2024-12-28 17:02:24 -05:00
140 lines
4.3 KiB
HTML
140 lines
4.3 KiB
HTML
<!DOCTYPE html>
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<html>
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<head>
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<meta charset="UTF-8">
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<title>Erik Liked To Dance</title>
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<link rel="stylesheet" href="../css/style.css">
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<script type="text/javascript" src="../../dist/paper-full.js"></script>
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<script type="text/paperscript" canvas="canvas">
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var leftPath = new Path({
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strokeColor: 'red',
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opacity: 0.5
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});
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var rightPath = new Path({
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strokeColor: 'green',
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opacity: 0.5
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});
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var amount = 8;
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var step = view.size.width / (amount + 1);
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var flip = false;
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for (var i = 0; i <= amount; i++) {
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leftPath.add(new Point(i * step, 0));
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rightPath.add(new Point(i * step, 0));
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}
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var group = new Group({
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children: [leftPath, rightPath],
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applyMatrix: false,
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strokeWidth: 30,
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strokeJoin: 'round',
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strokeCap: 'butt',
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pivot: leftPath.position,
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position: view.center
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});
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function onMouseDown() {
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flip = !flip;
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}
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function onKeyDown(event) {
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if (event.key === 'space')
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group.fullySelected = !group.fullySelected;
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}
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var audio, source, analyserL, analyserR, freqByteData;
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view.onFrame = function() {
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var step = view.size.width / (amount + 1);
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var scale = view.size.height / 1.5;
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analyserL.getByteFrequencyData(freqByteData);
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var leftBands = getEqualizerBands(freqByteData, true);
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analyserR.getByteFrequencyData(freqByteData);
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var rightBands = getEqualizerBands(freqByteData, true);
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for (var i = 1; i <= amount; i++) {
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leftPath.segments[i].point = [i * step, -leftBands[i - 1] * scale];
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rightPath.segments[i].point = [i * step, -rightBands[i - 1] * scale * (flip ? -1 : 1)];
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}
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leftPath.smooth();
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rightPath.smooth();
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group.pivot = [leftPath.position.x, 0];
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group.position = view.center;
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}
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// Pause animation until we have data
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view.pause();
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var AudioContext = window.AudioContext || window.webkitAudioContext;
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if (AudioContext) {
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audio = new AudioContext();
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source = audio.createBufferSource();
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// Create two separate analyzers for left and right channel.
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analyserL = audio.createAnalyser();
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analyserL.smoothingTimeConstant = 0.25;
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analyserL.fftSize = Math.pow(2, amount) * 2;
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analyserR = audio.createAnalyser();
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analyserR.smoothingTimeConstant = analyserL.smoothingTimeConstant;
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analyserR.fftSize = analyserL.fftSize;
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// Create the buffer to receive the analyzed data.
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freqByteData = new Uint8Array(analyserL.frequencyBinCount);
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// Create a splitter to feed them both
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var splitter = audio.createChannelSplitter();
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// Connect audio processing graph
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source.connect(splitter);
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splitter.connect(analyserL, 0, 0);
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splitter.connect(analyserR, 1, 0);
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// Connect source to output also so we can hear it
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source.connect(audio.destination);
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loadAudioBuffer('http://assets.paperjs.org/audio/gnossienne.mp3');
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} else {
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// TODO: Print error message
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alert('Audio not supported');
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}
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function loadAudioBuffer(url) {
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// Load asynchronously
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var request = new XMLHttpRequest();
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request.open("GET", url, true);
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request.responseType = "arraybuffer";
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request.onload = function() {
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audio.decodeAudioData(
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request.response,
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function(buffer) {
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source.buffer = buffer;
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source.loop = true;
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source.start(0);
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view.play();
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},
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function(buffer) {
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alert("Error loading MP3");
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}
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);
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};
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request.send();
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}
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function getEqualizerBands(data) {
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var bands = [];
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var amount = Math.sqrt(data.length) / 2;
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for (var i = 0; i < amount; i++) {
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var start = Math.pow(2, i) - 1;
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var end = start * 2 + 1;
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var sum = 0;
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for (var j = start; j < end; j++) {
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sum += data[j];
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}
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var avg = sum / (255 * (end - start));
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bands[i] = Math.sqrt(avg / Math.SQRT2);
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}
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return bands;
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}
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</script>
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</head>
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<body>
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<canvas id="canvas" resize></canvas>
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</body>
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</html>
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