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tfjs-tsne test
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| <canvas id=canvas width=960 height=500></canvas> | |
| <script src="https://unpkg.com/@tensorflow/tfjs"></script> | |
| <script src="https://unpkg.com/@tensorflow/tfjs-tsne"></script> | |
| <script> | |
| (async function() { | |
| const width = 960, | |
| height = (width * 2) / 3, | |
| context = document.getElementById("canvas").getContext("2d"); | |
| const data = tf.randomUniform([1024, 3]); | |
| const ts = tsne.tsne(data, { perplexity: 10 }); | |
| const knnIterations = ts.knnIterations(); | |
| // Do the KNN computation. This needs to complete before we run tsne | |
| for (let i = 0; i < knnIterations; ++i) { | |
| console.log("iterate Knn", i, "/", knnIterations); | |
| await ts.iterateKnn(); | |
| //yield ts.coordsArray(); | |
| } | |
| const tsneIterations = 100; | |
| for (let i = 0; i < tsneIterations; ++i) { | |
| await ts.iterate(10); | |
| // Draw the embedding here... | |
| draw(await ts.coordsArray()); | |
| } | |
| function draw(coords) { | |
| context.fillStyle= 'rgba(255,255,255,0.7)'; | |
| context.fillRect(0, 0, width, height); | |
| coords.forEach((point, i) => { | |
| context.beginPath(), | |
| context.arc(point[0] * width, point[1] * height, 8, 0, 2 * Math.PI), | |
| (context.fillStyle = `rgb(${data.get(i, 0) * 255},${data.get(i, 1) * | |
| 255},${data.get(i, 2) * 255})`), | |
| context.fill(); | |
| }); | |
| } | |
| })(); | |
| </script> |
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