Remove unused files
This commit is contained in:
Pitchaya Boonsarngsuk
@@ -1,195 +0,0 @@
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function doInterpolation(sampleSet, remainderSet, interpSubset, properties) {
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var distance = calculateDistancePoker;
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// var distance = calculateEuclideanDistance;
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console.log("Brute-force");
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for (var i = 0; i < remainderSet.length; i++) {
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var node = remainderSet[i],
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minNode = sampleSet[0],
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minDist = 0,
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sampleCache = [];
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minDist = distance(node, minNode, properties);
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for (var j = 1, sample; j < sampleSet.length; j++) {
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sample = sampleSet[j];
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if ((sample !== node) && (distance(node, sample, properties) < minDist)) {
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minDist = distance(node, sample, properties);
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minNode = sample;
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}
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}
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// console.log()
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for (var k = 0; k < interpSubset.length; k++) {
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sampleCache[k] = distance(node, interpSubset[k], properties);
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}
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var radius = distance(node, minNode, properties);
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placeNearToNearestNeighbour(node, minNode, interpSubset, sampleCache, radius);
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}
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}
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function placeNearToNearestNeighbour(node, minNode, sample, sampleCache, radius) {
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var
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dist0 = 0.0,
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dist90 = 0.0,
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dist180 = 0.0,
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dist270 = 0.0,
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lowBound = 0.0,
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highBound = 0.0;
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dist0 = sumDistToSample(node, centerPoint(0, radius, minNode.x, minNode.y), sample, sampleCache);
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dist90 = sumDistToSample(node, centerPoint(90, radius, minNode.x, minNode.y), sample, sampleCache);
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dist180 = sumDistToSample(node, centerPoint(180, radius, minNode.x, minNode.y), sample, sampleCache);
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dist270 = sumDistToSample(node, centerPoint(270, radius, minNode.x, minNode.y), sample, sampleCache);
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// console.log(dist0, dist90, dist180, dist270);
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// Determine the closest quadrant
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if (dist0 == dist180) {
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if (dist90 > dist270)
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lowBound = highBound = 270;
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else
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lowBound = highBound = 90;
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} else if (dist90 == dist270) {
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if (dist0 > dist180)
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lowBound = highBound = 180;
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else
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lowBound = highBound = 0;
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} else if (dist0 > dist180) {
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if (dist90 > dist270) {
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lowBound = 180;
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highBound = 270;
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} else {
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lowBound = 90;
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highBound = 180;
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}
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} else {
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if (dist90 > dist270) {
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lowBound = 270;
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highBound = 360;
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} else {
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lowBound = 0;
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highBound = 90;
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}
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}
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var angle = binarySearch(lowBound, highBound, minNode.x, minNode.y, radius, node, sample, sampleCache);
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var newPoint = centerPoint(angle, radius, minNode.x, minNode.y);
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// console.log(newPoint);
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node.x = newPoint.x;
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node.y = newPoint.y;
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// for (var i = 0; i < 20; i++) {
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// var forces = sumForcesToSample(node, sample, sampleCache);
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// // console.log(forces);
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// node.x += forces.x;
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// node.y += forces.y;
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// }
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}
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function centerPoint(angle, radius, posX, posY) {
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var x = posX + Math.cos(toRadians(angle) * radius);
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var y = posY + Math.sin(toRadians(angle) * radius);
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return {
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x: x,
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y: y
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};
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}
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function toRadians(degrees) {
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return degrees * (Math.PI / 180);
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}
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function sumDistToSample(node, point, sample, sampleCache) {
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var total = 0.0;
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// console.log(total, sample);
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for (var i = 0; i < sample.length; i++) {
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var s = sample[i];
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var realDist = Math.hypot(s.x - point.x, s.y - point.y);
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var desDist = sampleCache[i];
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total += Math.abs(realDist - desDist);
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}
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return total;
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}
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function sumForcesToSample(node, sample, sampleCache) {
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var x = 0,
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y = 0,
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// len = 0,
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dist = 0,
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force,
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SPRING_FORCE = 0.7;
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for (var i = 0, unitX, unitY; i < sample.length; i++) {
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var s = sample[i];
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if (s !== node) {
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unitX = s.x - node.x;
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unitY = s.y - node.y;
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// Normalize coordinates
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len = Math.sqrt(unitX * unitX + unitY * unitY);
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unitX /= len;
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unitY /= len;
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console.log(unitX, unitY);
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var realDist = Math.sqrt(unitX * unitX + unitY * unitY);
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var desDist = sampleCache[i];
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dist += realDist - desDist;
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force = (SPRING_FORCE * dist);
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x += unitX * force;
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y += unitY * force;
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}
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x *= (1.0 / sample.length);
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y *= (1.0 / sample.length);
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return {
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x: x,
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y: y
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};
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}
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}
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function binarySearch(lb, hb, x, y, r, node, sample, sampleCache) {
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while (lb <= hb) {
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var mid = Math.round((lb + hb) / 2);
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if ((mid === lb) || (mid === hb)) {
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if (sumDistToSample(node, centerPoint(lb, r, x, y), sample, sampleCache) >=
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sumDistToSample(node, centerPoint(hb, r, x, y), sample, sampleCache)) {
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return hb;
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} else {
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return lb;
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}
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} else {
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var distMidLeft = sumDistToSample(node, centerPoint(mid + 1, r, x, y), sample, sampleCache);
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var distMidRight = sumDistToSample(node, centerPoint(mid - 1, r, x, y), sample, sampleCache);
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var distMid = sumDistToSample(node, centerPoint(mid, r, x, y), sample, sampleCache);
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if (distMid > distMidLeft) {
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lb = mid + 1;
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} else if (distMid > distMidRight) {
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hb = mid - 1;
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} else {
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return mid;
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}
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}
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}
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return -1;
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}
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@@ -1,269 +0,0 @@
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function doInterpolationPivots(sampleSet, remainderSet, interpSubset, properties) {
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var distance = calculateDistancePoker;
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// var distance = calculateEuclideanDistance;
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// Pivot based parent finding
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var numBuckets = Math.floor(Math.sqrt(sampleSet.length)),
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// numPivots = Math.floor(Math.sqrt(sampleSet.length)),
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numPivots = 3,
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parents = [],
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maxDists = [],
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bucketWidths = [],
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pivotsBuckets = [];
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console.log("Parents, pivots=", numPivots);
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var pivots = createRandomSample(sampleSet.concat(remainderSet), sampleSet.length, numPivots);
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for (var i = 0; i < numPivots; i++) {
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pivotsBuckets[i] = [];
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for (var j = 0; j < numBuckets; j++) {
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pivotsBuckets[i][j] = [];
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}
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}
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// Pre-processing
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var fullDists = []
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for (var i = 0; i < sampleSet.length; i++) {
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fullDists[i] = [];
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}
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for (var j = 0, maxDist = -1; j < numPivots; j++) {
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var c1 = pivots[j];
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for (var i = 0; i < sampleSet.length; i++) {
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var c2 = sampleSet[i];
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if (c1 !== c2) {
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var dist = distance(c1, c2, properties);
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// console.log(dist, c1, c2);
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if (dist > maxDist) {
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maxDist = dist;
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}
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fullDists[i][j] = dist;
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} else {
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fullDists[i][j] = 0.0001;
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}
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}
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maxDists.push(maxDist);
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bucketWidths.push(maxDist / numBuckets);
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}
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// console.log(fullDists);
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for (var j = 0; j < numPivots; j++) {
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var bucketWidth = bucketWidths[j];
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for (var i = 0; i < sampleSet.length; i++) {
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var tmp = pivotsBuckets[j][Math.floor((fullDists[i][j] - 0.0001) / bucketWidth)];
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// pivotsBuckets[j][Math.floor((fullDists[i][j] - 0.0001) / bucketWidth)].push(sampleSet[i]);
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// console.log(tmp, i, j, bucketWidth, Math.floor((fullDists[i][j] - 0.0001) / bucketWidth));
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tmp.push(sampleSet[i]);
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}
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}
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for (var i = 0; i < remainderSet.length; i++) {
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var node = remainderSet[i],
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minNode = sampleSet[0],
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minDist = 0,
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sampleCache = [];
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// Pivot based parent search
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var node = remainderSet[i];
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var clDist = Number.MAX_VALUE;
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for (var p = 0; p < numPivots; p++) {
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var comp = pivots[p];
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var bucketWidth = bucketWidths[p];
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if (node !== comp) {
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var dist = distance(node, comp, properties);
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bNum = Math.floor((dist - 0.0001) / bucketWidth);
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if (bNum >= numBuckets) {
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bNum = numBuckets - 1;
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} else if (bNum < 0) {
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bNum = 0;
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}
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var bucketContents = pivotsBuckets[p][bNum];
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for (var w = 0; w < bucketContents.length; w++) {
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var c1 = bucketContents[w];
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if (c1 != node) {
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dist = distance(c1, node, properties);
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if (dist <= clDist) {
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clDist = dist;
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minNode = bucketContents[w];
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}
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}
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}
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}
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}
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for (var k = 0; k < interpSubset.length; k++) {
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sampleCache[k] = distance(node, interpSubset[k], properties);
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}
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var radius = distance(node, minNode, properties);
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placeNearToNearestNeighbour(node, minNode, interpSubset, sampleCache, radius);
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}
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}
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function placeNearToNearestNeighbour(node, minNode, sample, sampleCache, radius) {
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var
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dist0 = 0.0,
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dist90 = 0.0,
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dist180 = 0.0,
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dist270 = 0.0,
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lowBound = 0.0,
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highBound = 0.0;
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dist0 = sumDistToSample(node, centerPoint(0, radius, minNode.x, minNode.y), sample, sampleCache);
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dist90 = sumDistToSample(node, centerPoint(90, radius, minNode.x, minNode.y), sample, sampleCache);
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dist180 = sumDistToSample(node, centerPoint(180, radius, minNode.x, minNode.y), sample, sampleCache);
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dist270 = sumDistToSample(node, centerPoint(270, radius, minNode.x, minNode.y), sample, sampleCache);
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// console.log(dist0, dist90, dist180, dist270);
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// Determine the closest quadrant
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if (dist0 == dist180) {
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if (dist90 > dist270)
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lowBound = highBound = 270;
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else
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lowBound = highBound = 90;
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} else if (dist90 == dist270) {
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if (dist0 > dist180)
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lowBound = highBound = 180;
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else
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lowBound = highBound = 0;
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} else if (dist0 > dist180) {
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if (dist90 > dist270) {
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lowBound = 180;
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highBound = 270;
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} else {
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lowBound = 90;
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highBound = 180;
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}
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} else {
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if (dist90 > dist270) {
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lowBound = 270;
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highBound = 360;
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} else {
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lowBound = 0;
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highBound = 90;
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}
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}
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var angle = binarySearch(lowBound, highBound, minNode.x, minNode.y, radius, node, sample, sampleCache);
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var newPoint = centerPoint(angle, radius, minNode.x, minNode.y);
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// console.log(newPoint);
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node.x = newPoint.x;
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node.y = newPoint.y;
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// for (var i = 0; i < 20; i++) {
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// var forces = sumForcesToSample(node, sample, sampleCache);
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// // console.log(forces);
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// node.x += forces.x;
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// node.y += forces.y;
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// }
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}
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function centerPoint(angle, radius, posX, posY) {
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var x = posX + Math.cos(toRadians(angle) * radius);
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var y = posY + Math.sin(toRadians(angle) * radius);
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return {
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x: x,
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y: y
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};
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}
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function toRadians(degrees) {
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return degrees * (Math.PI / 180);
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}
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function sumDistToSample(node, point, sample, sampleCache) {
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var total = 0.0;
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// console.log(total, sample);
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for (var i = 0; i < sample.length; i++) {
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var s = sample[i];
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var realDist = Math.hypot(s.x - point.x, s.y - point.y);
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var desDist = sampleCache[i];
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total += Math.abs(realDist - desDist);
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}
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return total;
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}
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function sumForcesToSample(node, sample, sampleCache) {
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var x = 0,
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y = 0,
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// len = 0,
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dist = 0,
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force,
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SPRING_FORCE = 0.7;
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for (var i = 0, unitX, unitY; i < sample.length; i++) {
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var s = sample[i];
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if (s !== node) {
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unitX = s.x - node.x;
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unitY = s.y - node.y;
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// Normalize coordinates
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len = Math.sqrt(unitX * unitX + unitY * unitY);
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unitX /= len;
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unitY /= len;
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console.log(unitX, unitY);
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var realDist = Math.sqrt(unitX * unitX + unitY * unitY);
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var desDist = sampleCache[i];
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dist += realDist - desDist;
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force = (SPRING_FORCE * dist);
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x += unitX * force;
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y += unitY * force;
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}
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x *= (1.0 / sample.length);
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y *= (1.0 / sample.length);
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return {
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x: x,
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y: y
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};
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}
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}
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function binarySearch(lb, hb, x, y, r, node, sample, sampleCache) {
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while (lb <= hb) {
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var mid = Math.round((lb + hb) / 2);
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if ((mid === lb) || (mid === hb)) {
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if (sumDistToSample(node, centerPoint(lb, r, x, y), sample, sampleCache) >=
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sumDistToSample(node, centerPoint(hb, r, x, y), sample, sampleCache)) {
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return hb;
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} else {
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return lb;
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}
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} else {
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var distMidLeft = sumDistToSample(node, centerPoint(mid + 1, r, x, y), sample, sampleCache);
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var distMidRight = sumDistToSample(node, centerPoint(mid - 1, r, x, y), sample, sampleCache);
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var distMid = sumDistToSample(node, centerPoint(mid, r, x, y), sample, sampleCache);
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if (distMid > distMidLeft) {
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lb = mid + 1;
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} else if (distMid > distMidRight) {
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hb = mid - 1;
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} else {
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return mid;
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}
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}
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}
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return -1;
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}
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@@ -1,579 +0,0 @@
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// Get the width and heigh of the SVG element.
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var width = +document.getElementById('svg').clientWidth,
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height = +document.getElementById('svg').clientHeight;
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var svg = d3.select("svg")
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.call(d3.zoom().scaleExtent([0.0001, 1000000]).on("zoom", function () {
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svg.attr("transform", d3.event.transform);
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}))
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.append("g");
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var div = d3.select("body").append("div")
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.attr("class", "tooltip")
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.style("opacity", 0);
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var brush = d3.brush()
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.extent([[-9999999, -9999999], [9999999, 9999999]])
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.on("end", brushEnded);
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svg.append("g")
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.attr("class", "brush")
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.call(brush);
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var intercom = Intercom.getInstance();
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intercom.on("select", unSelectNodes);
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var imgs = svg.selectAll("image");
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var links = [],
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nodes,
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node,
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props,
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norm,
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p1 = 0,
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p2 = 0,
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size,
|
||||
distanceFunction,
|
||||
simulation,
|
||||
velocities = [],
|
||||
rendering = true, // Rendering during the execution.
|
||||
forceName = "forces",
|
||||
springForce = false,
|
||||
tooltipWidth = 0,
|
||||
fileName = "",
|
||||
selectedData,
|
||||
clickedIndex = -1;
|
||||
|
||||
// Default parameters
|
||||
var MULTIPLIER = 50,
|
||||
PERPLEXITY = 30,
|
||||
LEARNING_RATE = 10,
|
||||
NEIGHBOUR_SIZE = 6,
|
||||
SAMPLE_SIZE = 3,
|
||||
PIVOTS = false,
|
||||
NUM_PIVOTS = 3,
|
||||
ITERATIONS = 300,
|
||||
FULL_ITERATIONS = 20,
|
||||
NODE_SIZE = 10,
|
||||
COLOR_ATTRIBUTE = "";
|
||||
|
||||
// Create a color scheme for a range of numbers.
|
||||
var color = d3.scaleOrdinal(d3.schemeCategory10);
|
||||
|
||||
/**
|
||||
* Parse the data from the provided csv file using Papa Parse library
|
||||
* @param {file} evt - csv file.
|
||||
*/
|
||||
function parseFile(evt) {
|
||||
// Clear the previous nodes
|
||||
d3.selectAll(".nodes").remove();
|
||||
springForce = false;
|
||||
|
||||
fileName = evt.target.files[0].name;
|
||||
|
||||
Papa.parse(evt.target.files[0], {
|
||||
header: true,
|
||||
dynamicTyping: true,
|
||||
skipEmptyLines: true,
|
||||
complete: function (results) {
|
||||
processData(results.data, results.error);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Process the data and pass it into D3 force simulation.
|
||||
* @param {array} data
|
||||
* @param {object} error
|
||||
*/
|
||||
function processData(data, error) {
|
||||
if (error) throw error.message;
|
||||
|
||||
nodes = data;
|
||||
|
||||
// Number of iterations before stopping.
|
||||
size = nodes.length;
|
||||
|
||||
console.log("Number of iterations: ", ITERATIONS);
|
||||
|
||||
// Start by placing the nodes at the center (its starting positions).
|
||||
simulation = d3.forceSimulation();
|
||||
|
||||
console.log("n =", nodes.length);
|
||||
|
||||
// Calculate normalization arguments and get the list of
|
||||
// properties of the nodes.
|
||||
norm = calculateNormalization(nodes);
|
||||
props = Object.keys(nodes[0]);
|
||||
COLOR_ATTRIBUTE = props[0];
|
||||
|
||||
var opts = document.getElementById('color_attr').options;
|
||||
|
||||
props.forEach(function (d) {
|
||||
opts.add(new Option(d, d, (d === COLOR_ATTRIBUTE) ? true : false));
|
||||
});
|
||||
|
||||
// Add the nodes to DOM.
|
||||
node = svg.append("g")
|
||||
.attr("class", "nodes")
|
||||
.selectAll("circle")
|
||||
.data(nodes)
|
||||
.enter().append("circle")
|
||||
.attr("r", NODE_SIZE)
|
||||
.attr("transform", "translate(" + width / 2 + "," + height / 2 + ")")
|
||||
// Color code the data points by a property (for Poker Hands,
|
||||
// it is a CLASS property).
|
||||
.attr("fill", function (d) {
|
||||
return color(d[COLOR_ATTRIBUTE]);
|
||||
})
|
||||
.on("mouseover", function (d) {
|
||||
highlightOnHover(d[COLOR_ATTRIBUTE]);
|
||||
})
|
||||
.on("mouseout", function (d) {
|
||||
div.transition()
|
||||
.duration(500)
|
||||
.style("opacity", 0);
|
||||
node.attr("opacity", 1);
|
||||
})
|
||||
.on("click", function (d) {
|
||||
if (clickedIndex !== d.index) {
|
||||
highlightNeighbours(d.index, springForce ? Array.from(simulation.force(forceName).nodeNeighbours(d.index).keys()) : []);
|
||||
clickedIndex = d.index;
|
||||
} else {
|
||||
svg.selectAll("image").remove();
|
||||
node.attr("r", NODE_SIZE).attr("stroke-width", 0);
|
||||
clickedIndex = -1;
|
||||
}
|
||||
});
|
||||
|
||||
// Pass the nodes to the D3 force simulation.
|
||||
simulation
|
||||
.nodes(nodes)
|
||||
.on("tick", ticked)
|
||||
.on("end", ended);
|
||||
|
||||
function ticked() {
|
||||
// If rendering is selected, then draw at every iteration.
|
||||
if (rendering === true) {
|
||||
node
|
||||
.attr("cx", function (d) {
|
||||
return d.x;
|
||||
})
|
||||
.attr("cy", function (d) {
|
||||
return d.y;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
function ended() {
|
||||
if (rendering !== true) {
|
||||
node
|
||||
.attr("cx", function (d) {
|
||||
return d.x;
|
||||
})
|
||||
.attr("cy", function (d) {
|
||||
return d.y;
|
||||
});
|
||||
}
|
||||
|
||||
if (p1 !== 0) {
|
||||
// Performance time measurement
|
||||
p2 = performance.now();
|
||||
console.log("Execution time: " + (p2 - p1));
|
||||
// Do not calculate stress for data sets bigger than 100 000.
|
||||
// if (nodes.length <= 100000) {
|
||||
// console.log("Stress: ", simulation.force(forceName).stress());
|
||||
// }
|
||||
p1 = 0;
|
||||
p2 = 0;
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
function brushEnded() {
|
||||
var s = d3.event.selection,
|
||||
results = [];
|
||||
|
||||
if (s) {
|
||||
|
||||
var x0 = s[0][0] - width / 2,
|
||||
y0 = s[0][1] - height / 2,
|
||||
x1 = s[1][0] - width / 2,
|
||||
y1 = s[1][1] - height / 2;
|
||||
|
||||
if (nodes) {
|
||||
var sel = node.filter(function (d) {
|
||||
if (d.x > x0 && d.x < x1 && d.y > y0 && d.y < y1) {
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
}).data();
|
||||
|
||||
results = sel.map(function (a) { return a.index; });
|
||||
}
|
||||
|
||||
intercom.emit("select", { name: fileName, indices: results });
|
||||
|
||||
d3.select(".brush").call(brush.move, null);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Initialize the Chalmers' 1996 algorithm and start simulation.
|
||||
*/
|
||||
function startNeighbourSamplingSimulation() {
|
||||
springForce = true;
|
||||
simulation.stop();
|
||||
p1 = performance.now();
|
||||
|
||||
simulation
|
||||
.alphaDecay(1 - Math.pow(0.001, 1 / ITERATIONS))
|
||||
.force(forceName, d3.forceNeighbourSamplingDistance()
|
||||
// Set the parameters for the algorithm (optional).
|
||||
.neighbourSize(NEIGHBOUR_SIZE)
|
||||
.sampleSize(SAMPLE_SIZE)
|
||||
.multiplier(MULTIPLIER)
|
||||
// The distance function that will be used to calculate distances
|
||||
// between nodes.
|
||||
.distance(function (s, t) {
|
||||
return distanceFunction(s, t, props, norm);
|
||||
}));
|
||||
// Restart the simulation.
|
||||
console.log(simulation.force(forceName).neighbourSize(), simulation.force(forceName).sampleSize());
|
||||
simulation.alpha(1).restart();
|
||||
}
|
||||
|
||||
/**
|
||||
* Initialize the hybrid layout algorithm and start simulation.
|
||||
*/
|
||||
function startHybridSimulation() {
|
||||
springForce = false;
|
||||
d3.selectAll(".nodes").remove();
|
||||
simulation.stop();
|
||||
p1 = performance.now();
|
||||
|
||||
hybridSimulation = d3.hybridSimulation(nodes);
|
||||
|
||||
hybridSimulation
|
||||
.multiplier(MULTIPLIER)
|
||||
.sampleIterations(ITERATIONS)
|
||||
.pivots(PIVOTS)
|
||||
.numPivots(NUM_PIVOTS)
|
||||
.fullIterations(FULL_ITERATIONS)
|
||||
.neighbourSize(NEIGHBOUR_SIZE)
|
||||
.sampleSize(SAMPLE_SIZE);
|
||||
|
||||
var sample = hybridSimulation.sample();
|
||||
var remainder = hybridSimulation.remainder();
|
||||
|
||||
// Add the nodes to DOM.
|
||||
node = svg.append("g")
|
||||
.attr("class", "nodes")
|
||||
.selectAll("circle")
|
||||
.data(sample)
|
||||
.enter().append("circle")
|
||||
.attr("r", NODE_SIZE)
|
||||
.attr("transform", "translate(" + width / 2 + "," + height / 2 + ")")
|
||||
// Color code the data points by a property (for Poker Hands,
|
||||
// it is a CLASS property).
|
||||
.attr("fill", function (d) {
|
||||
return color(d[COLOR_ATTRIBUTE])
|
||||
})
|
||||
.on("mouseover", function (d) {
|
||||
div.transition()
|
||||
.duration(200)
|
||||
.style("opacity", .9);
|
||||
div.html(formatTooltip(d))
|
||||
.style("left", (d3.event.pageX) + "px")
|
||||
.style("top", (d3.event.pageY - (15 * props.length)) + "px")
|
||||
.style("width", (6 * tooltipWidth) + "px")
|
||||
.style("height", (14 * props.length) + "px");
|
||||
highlightOnHover(d[COLOR_ATTRIBUTE]);
|
||||
})
|
||||
.on("mouseout", function (d) {
|
||||
div.transition()
|
||||
.duration(500)
|
||||
.style("opacity", 0);
|
||||
node.attr("opacity", 1);
|
||||
});
|
||||
|
||||
if (selectedData) {
|
||||
unSelectNodes(selectedData);
|
||||
}
|
||||
|
||||
hybridSimulation
|
||||
.distance(distanceFunction);
|
||||
|
||||
hybridSimulation
|
||||
.on("sampleTick", tickedHybrid)
|
||||
.on("fullTick", tickedHybrid)
|
||||
.on("startFull", started)
|
||||
.on("end", endedHybrid);
|
||||
|
||||
|
||||
function tickedHybrid() {
|
||||
if (rendering === true) {
|
||||
node
|
||||
.attr("cx", function (d) {
|
||||
return d.x;
|
||||
})
|
||||
.attr("cy", function (d) {
|
||||
return d.y;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
function started() {
|
||||
d3.selectAll(".nodes").remove();
|
||||
// Add the nodes to DOM.
|
||||
node = svg.append("g")
|
||||
.attr("class", "nodes")
|
||||
.selectAll("circle")
|
||||
.data(nodes)
|
||||
.enter().append("circle")
|
||||
.attr("r", NODE_SIZE)
|
||||
.attr("transform", "translate(" + width / 2 + "," + height / 2 + ")")
|
||||
// Color code the data points by a property (for Poker Hands,
|
||||
// it is a CLASS property).
|
||||
.attr("fill", function (d) {
|
||||
return color(d[COLOR_ATTRIBUTE])
|
||||
})
|
||||
.on("mouseover", function (d) {
|
||||
div.transition()
|
||||
.duration(200)
|
||||
.style("opacity", .9);
|
||||
div.html(formatTooltip(d))
|
||||
.style("left", (d3.event.pageX) + "px")
|
||||
.style("top", (d3.event.pageY - (15 * props.length)) + "px")
|
||||
.style("width", (6 * tooltipWidth) + "px")
|
||||
.style("height", (14 * props.length) + "px");
|
||||
highlightOnHover(d[COLOR_ATTRIBUTE]);
|
||||
})
|
||||
.on("mouseout", function (d) {
|
||||
div.transition()
|
||||
.duration(500)
|
||||
.style("opacity", 0);
|
||||
node.attr("opacity", 1);
|
||||
});
|
||||
|
||||
if (selectedData) {
|
||||
unSelectNodes(selectedData);
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
||||
function endedHybrid() {
|
||||
if (rendering !== true) {
|
||||
node
|
||||
.attr("cx", function (d) {
|
||||
return d.x;
|
||||
})
|
||||
.attr("cy", function (d) {
|
||||
return d.y;
|
||||
});
|
||||
}
|
||||
|
||||
// Performance time measurement
|
||||
p2 = performance.now();
|
||||
console.log("Execution time: " + (p2 - p1));
|
||||
// Do not calculate stress for data sets bigger than 100 000.
|
||||
// if (nodes.length <= 100000) {
|
||||
// console.log("Stress: ", hybridSimulation.stress());
|
||||
// }
|
||||
p1 = 0;
|
||||
p2 = 0;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Initialize the t-SNE algorithm and start simulation.
|
||||
*/
|
||||
function starttSNE() {
|
||||
springForce = false;
|
||||
simulation.stop();
|
||||
p1 = performance.now();
|
||||
|
||||
simulation
|
||||
.alphaDecay(1 - Math.pow(0.001, 1 / ITERATIONS))
|
||||
.force(forceName, d3.tSNE()
|
||||
// Set the parameter for the algorithm (optional).
|
||||
.perplexity(PERPLEXITY)
|
||||
.learningRate(LEARNING_RATE)
|
||||
// The distance function that will be used to calculate distances
|
||||
// between nodes.
|
||||
.distance(function (s, t) {
|
||||
return distanceFunction(s, t, props, norm) * MULTIPLIER;
|
||||
}));
|
||||
// Restart the simulation.
|
||||
console.log(simulation.force(forceName).perplexity(), simulation.force(forceName).learningRate());
|
||||
simulation.alpha(1).restart();
|
||||
}
|
||||
|
||||
/**
|
||||
* Initialize the Barnes-Hut algorithm and start simulation.
|
||||
*/
|
||||
function startBarnesHutSimulation() {
|
||||
springForce = false;
|
||||
simulation.stop();
|
||||
p1 = performance.now();
|
||||
|
||||
simulation
|
||||
.alphaDecay(1 - Math.pow(0.001, 1 / ITERATIONS))
|
||||
.force(forceName, d3.forceBarnesHut()
|
||||
// The distance function that will be used to calculate distances
|
||||
// between nodes.
|
||||
.distance(function (s, t) {
|
||||
return distanceFunction(s, t, props, norm) * MULTIPLIER;
|
||||
}));
|
||||
// Restart the simulation.
|
||||
simulation.alpha(1).restart();
|
||||
}
|
||||
|
||||
/**
|
||||
* Initialize the link force algorithm and start simulation.
|
||||
*/
|
||||
function startLinkSimulation() {
|
||||
springForce = false;
|
||||
simulation.stop();
|
||||
p1 = performance.now();
|
||||
|
||||
// Initialize link array.
|
||||
nodes = simulation.nodes();
|
||||
for (i = 0; i < nodes.length; i++) {
|
||||
for (j = 0; j < nodes.length; j++) {
|
||||
if (i !== j) {
|
||||
links.push({
|
||||
source: nodes[i],
|
||||
target: nodes[j],
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Add the links to the simulation.
|
||||
simulation.force(forceName, d3.forceLink().links(links));
|
||||
|
||||
simulation
|
||||
.alphaDecay(1 - Math.pow(0.001, 1 / ITERATIONS))
|
||||
.force(forceName)
|
||||
// The distance function that will be used to calculate distances
|
||||
// between nodes.
|
||||
.distance(function (n) {
|
||||
return distanceFunction(n.source, n.target, props, norm) * MULTIPLIER;
|
||||
})
|
||||
// Set the parameter for the algorithm (optional).
|
||||
.strength(1);
|
||||
// Restart the simulation.
|
||||
simulation.alpha(1).restart();
|
||||
}
|
||||
|
||||
/**
|
||||
* Halt the execution.
|
||||
*/
|
||||
function stopSimulation() {
|
||||
simulation.stop();
|
||||
if (typeof hybridSimulation !== 'undefined') {
|
||||
hybridSimulation.stop();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate the average values of the array.
|
||||
* @param {array} array
|
||||
* @return {number} the mean of the array.
|
||||
*/
|
||||
function getAverage(array) {
|
||||
var total = 0;
|
||||
for (var i = 0; i < array.length; i++) {
|
||||
total += array[i];
|
||||
}
|
||||
return total / array.length;
|
||||
}
|
||||
|
||||
/**
|
||||
* Deselect the nodes to match the selection from other window.
|
||||
* @param {*} data
|
||||
*/
|
||||
function unSelectNodes(data) {
|
||||
|
||||
selectedData = data;
|
||||
|
||||
if (fileName === data.name && nodes) {
|
||||
node
|
||||
.classed("notSelected", function (d) {
|
||||
if (data.indices.indexOf(d.index) < 0) {
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Highlight the neighbours for neighbour and sampling algorithm and show the corresponding MNIST images for each node.
|
||||
* @param {*} indices
|
||||
*/
|
||||
function highlightNeighbours(index, indices) {
|
||||
var selectedNodes = [nodes[index]];
|
||||
indices.forEach(function (i) {
|
||||
selectedNodes.push(nodes[i]);
|
||||
});
|
||||
|
||||
var ratio = NODE_SIZE / 10;
|
||||
|
||||
svg.selectAll("image").remove();
|
||||
imgs.data(selectedNodes).enter()
|
||||
.append("svg:image")
|
||||
.attr("transform", "translate(" + width / 2 + "," + height / 2 + ")")
|
||||
.attr("xlink:href", function (d) {
|
||||
return "data/mnist/images/" + d.index + ".png";
|
||||
})
|
||||
.attr("x", function (d) {
|
||||
return d.x + (ratio * 20);
|
||||
})
|
||||
.attr("y", function (d) {
|
||||
return d.y - (ratio * 20);
|
||||
})
|
||||
.attr("width", ratio * 28)
|
||||
.attr("height", ratio * 28);
|
||||
|
||||
|
||||
node
|
||||
.attr("r", function (d) {
|
||||
if (indices.indexOf(d.index) >= 0) {
|
||||
return NODE_SIZE * 2;
|
||||
}
|
||||
return NODE_SIZE;
|
||||
})
|
||||
.attr("stroke-width", function (d) {
|
||||
if (indices.indexOf(d.index) >= 0) {
|
||||
return NODE_SIZE * 0.2 + "px";
|
||||
}
|
||||
return "0px";
|
||||
})
|
||||
.attr("stroke", "white");
|
||||
}
|
||||
|
||||
/**
|
||||
* Highlight all the nodes with the same class on hover
|
||||
* @param {*} highlighValue
|
||||
*/
|
||||
function highlightOnHover(highlighValue) {
|
||||
node.attr("opacity", function (d) {
|
||||
return (highlighValue === d[COLOR_ATTRIBUTE]) ? 1 : 0.3;
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Color the nodes according to given attribute.
|
||||
*/
|
||||
function colorToAttribute() {
|
||||
node.attr("fill", function (d) {
|
||||
return color(d[COLOR_ATTRIBUTE])
|
||||
});
|
||||
}
|
||||
@@ -1,109 +0,0 @@
|
||||
function findPivots(dataSet, sampleSet, remainderSet) {
|
||||
var distance = calculateDistancePoker;
|
||||
// Initialize
|
||||
|
||||
var numBuckets = Math.floor(Math.sqrt(sampleSet.length)),
|
||||
numPivots = Math.floor(Math.sqrt(sampleSet.length)),
|
||||
parents = [],
|
||||
maxDists = [],
|
||||
bucketWidths = [],
|
||||
pivotsBuckets = [];
|
||||
|
||||
var pivots = createRandomSample(dataSet, sampleSet.length, numPivots);
|
||||
|
||||
for (var i = 0; i < numPivots; i++) {
|
||||
pivotsBuckets[i] = [];
|
||||
for (var j = 0; j < numBuckets; j++) {
|
||||
pivotsBuckets[i][j] = [];
|
||||
}
|
||||
}
|
||||
|
||||
// Pre-processing
|
||||
var fullDists = []
|
||||
for (var i = 0; i < sampleSet.length; i++) {
|
||||
fullDists[i] = [];
|
||||
}
|
||||
|
||||
for (var j = 0, maxDist = -1; j < numPivots; j++) {
|
||||
var c1 = pivots[j];
|
||||
for (var i = 0; i < sampleSet.length; i++) {
|
||||
var c2 = sampleSet[i];
|
||||
if (c1 !== c2) {
|
||||
var dist = distance(c1, c2);
|
||||
// console.log(dist, c1, c2);
|
||||
if (dist > maxDist) {
|
||||
maxDist = dist;
|
||||
}
|
||||
fullDists[i][j] = dist;
|
||||
} else {
|
||||
fullDists[i][j] = 0.0001;
|
||||
}
|
||||
}
|
||||
maxDists.push(maxDist);
|
||||
bucketWidths.push(maxDist / numBuckets);
|
||||
}
|
||||
|
||||
// console.log(fullDists);
|
||||
|
||||
for (var j = 0; j < numPivots; j++) {
|
||||
var bucketWidth = bucketWidths[j];
|
||||
for (var i = 0; i < sampleSet.length; i++) {
|
||||
var tmp = pivotsBuckets[j][Math.floor((fullDists[i][j] - 0.0001) / bucketWidth)];
|
||||
// pivotsBuckets[j][Math.floor((fullDists[i][j] - 0.0001) / bucketWidth)].push(sampleSet[i]);
|
||||
// console.log(tmp, i, j, bucketWidth, Math.floor((fullDists[i][j] - 0.0001) / bucketWidth));
|
||||
tmp.push(sampleSet[i]);
|
||||
}
|
||||
}
|
||||
|
||||
// Find parents
|
||||
for (var r = 0, bNum, minIndex; r < remainderSet.length; r++) {
|
||||
var node = remainderSet[r];
|
||||
var clDist = Number.MAX_VALUE;
|
||||
for (var p = 0; p < numPivots; p++) {
|
||||
var comp = pivots[p];
|
||||
var bucketWidth = bucketWidths[p];
|
||||
if (node !== comp) {
|
||||
var dist = distance(node, comp);
|
||||
bNum = Math.floor((dist - 0.0001) / bucketWidth);
|
||||
if (bNum >= numBuckets) {
|
||||
bNum = numBuckets - 1;
|
||||
} else if (bNum < 0) {
|
||||
bNum = 0;
|
||||
}
|
||||
var bucketContents = pivotsBuckets[p][bNum];
|
||||
for (var w = 0; w < bucketContents.length; w++) {
|
||||
var c1 = bucketContents[w];
|
||||
if (c1 != node) {
|
||||
dist = distance(c1, node);
|
||||
if (dist <= clDist) {
|
||||
clDist = dist;
|
||||
minIndex = bucketContents[w];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
parents.push(minIndex);
|
||||
}
|
||||
return parents;
|
||||
}
|
||||
|
||||
function createRandomSample(nodes, max, size) {
|
||||
var randElements = [];
|
||||
|
||||
for (var i = 0; i < size; ++i) {
|
||||
// Stop when no new elements can be found.
|
||||
if (randElements.size >= nodes.length) {
|
||||
break;
|
||||
}
|
||||
var rand = Math.floor((Math.random() * max));
|
||||
// If the rand is already in random list or in exclude list
|
||||
// ignore it and get a new value.
|
||||
while (randElements.includes(rand)) {
|
||||
rand = Math.floor((Math.random() * max));
|
||||
}
|
||||
randElements.push(nodes[rand]);
|
||||
}
|
||||
|
||||
return randElements;
|
||||
}
|
||||
@@ -1,274 +0,0 @@
|
||||
<!DOCTYPE html>
|
||||
<html>
|
||||
<meta charset="utf-8">
|
||||
<style>
|
||||
h1 {
|
||||
text-align: center;
|
||||
margin: 10px 0 10px 0;
|
||||
}
|
||||
|
||||
.links line {
|
||||
stroke: #999;
|
||||
stroke-opacity: 0.6;
|
||||
}
|
||||
/*.nodes circle {
|
||||
stroke: #fff;
|
||||
stroke-width: 1.5px;
|
||||
}*/
|
||||
|
||||
circle:hover {
|
||||
fill: #8B0000;
|
||||
opacity: 0.8;
|
||||
}
|
||||
|
||||
.notSelected {
|
||||
fill: #999;
|
||||
opacity: 0.8;
|
||||
}
|
||||
|
||||
.highlighted {
|
||||
fill: black;
|
||||
}
|
||||
|
||||
#svg {
|
||||
border-style: solid;
|
||||
margin: auto;
|
||||
}
|
||||
|
||||
.left {
|
||||
float: left;
|
||||
width: 32%;
|
||||
}
|
||||
|
||||
.controls {
|
||||
flex-basis: 200px;
|
||||
padding: 0 5px;
|
||||
}
|
||||
|
||||
.controls input[type="range"] {
|
||||
margin: 0 5% 0.5em 5%;
|
||||
width: 90%;
|
||||
}
|
||||
|
||||
.multiplier {
|
||||
margin: 10px 0 10px 0;
|
||||
}
|
||||
|
||||
.parameters {
|
||||
margin: 10px 0 10px 30px;
|
||||
}
|
||||
|
||||
.checkbox {
|
||||
margin: 10px 0 10px 0;
|
||||
}
|
||||
|
||||
.start {
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
div.tooltip {
|
||||
position: absolute;
|
||||
border: 0px;
|
||||
border-radius: 8px;
|
||||
pointer-events: none;
|
||||
}
|
||||
</style>
|
||||
|
||||
<body>
|
||||
<h1>Evaluation</h1>
|
||||
<svg id="svg" width="100%" height="600">
|
||||
<div class="left controls">
|
||||
|
||||
<div class="input">
|
||||
<input type="file" id="csv-file" name="files">
|
||||
</div>
|
||||
|
||||
<div class="multiplier">
|
||||
<label title="The size of the nodes">
|
||||
Node size
|
||||
<output id="nodeSizeSliderOutput">10</output>
|
||||
<input type="range" min="5" max="200" value="10" step="5" oninput="d3.select('#nodeSizeSliderOutput').text(value); NODE_SIZE=value; d3.selectAll('circle').attr('r', value);">
|
||||
</label>
|
||||
<br/>
|
||||
<label title="The number that distance is multiplied by in order to improve the visibility of the graph">
|
||||
distanceMultiplier
|
||||
<output id="distanceMultiplierSliderOutput">50</output>
|
||||
<input type="range" min="5" max="1000" value="50" step="5" oninput="d3.select('#distanceMultiplierSliderOutput').text(value); MULTIPLIER=value;">
|
||||
</label>
|
||||
<br/>
|
||||
<label title="Number of iterations before the simulation is stopped">
|
||||
Iterations
|
||||
<output id="iterationsSliderOutput">300</output>
|
||||
<input type="range" min="5" max="5000" value="300" step="5" oninput="d3.select('#iterationsSliderOutput').text(value); ITERATIONS=value;">
|
||||
</label>
|
||||
<br/>
|
||||
<label title="Attribute used for coloring nodes">
|
||||
Color attribute
|
||||
<select id="color_attr" onchange="COLOR_ATTRIBUTE=value; colorToAttribute();">
|
||||
</select>
|
||||
</label>
|
||||
</div>
|
||||
|
||||
<div class="checkbox">
|
||||
<label title="js/">
|
||||
Rendering
|
||||
<input type="checkbox" checked onclick="rendering=!rendering;">
|
||||
</label>
|
||||
</div>
|
||||
|
||||
<div class="start">
|
||||
<button id="startSimulation" form="algorithmForm">Start</button>
|
||||
<button onclick="stopSimulation()">Stop</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="left">
|
||||
<p>Select algorithm:</p>
|
||||
<div id="algorithms">
|
||||
<input id="HLButton" type="radio" name="algorithm" onclick="d3.select('#startSimulation').on('click', startHybridSimulation)">Hybrid
|
||||
layout
|
||||
<br>
|
||||
<div id="HLParameters" class="parameters" style="display:none">
|
||||
<div id="pivots">
|
||||
<input id="BFButton" type="radio" name="pivots" checked="checked" onclick="PIVOTS=false;">Brute-force<br>
|
||||
<input id="PButton" type="radio" name="pivots" onclick="PIVOTS=true;">Pivots<br>
|
||||
<div id="numPivots" class="parameters" style="display:none">
|
||||
<label title="The number of pivots">
|
||||
Number of Pivots
|
||||
<output id="numPivotsSliderOutput">3</output><br/>
|
||||
<input type="range" min="1" max="50" value="3" step="1" oninput="d3.select('#numPivotsSliderOutput').text(value); NUM_PIVOTS=value;">
|
||||
</label>
|
||||
</div>
|
||||
</div>
|
||||
<br/>
|
||||
<label title="Number of iterations done at the end">
|
||||
Full iterations
|
||||
<output id="fullIterationsSliderOutput">20</output><br/>
|
||||
<input type="range" min="1" max="100" value="20" step="1" oninput="d3.select('#fullIterationsSliderOutput').text(value); FULL_ITERATIONS=value;">
|
||||
</label>
|
||||
<br/>
|
||||
<label title="NeighbourSize">
|
||||
Neighbour Set
|
||||
<output id="hlneighbourSizeSliderOutput">6</output><br/>
|
||||
<input type="range" min="1" max="100" value="6" step="1" oninput="d3.select('#hlneighbourSizeSliderOutput').text(value); NEIGHBOUR_SIZE=value;">
|
||||
</label>
|
||||
<br/>
|
||||
<label title="SampleSize">
|
||||
Sample Set
|
||||
<output id="hlsampleSizeSliderOutput">3</output><br/>
|
||||
<input type="range" min="1" max="100" value="3" step="1" oninput="d3.select('#hlsampleSizeSliderOutput').text(value); SAMPLE_SIZE=value;">
|
||||
</label>
|
||||
</div>
|
||||
|
||||
<input id="NSButton" type="radio" name="algorithm" onclick="d3.select('#startSimulation').on('click', startNeighbourSamplingSimulation)">Neighbour
|
||||
and Sampling<br>
|
||||
<div id="NSParameters" class="parameters" style="display:none">
|
||||
<label title="NeighbourSize">
|
||||
Neighbour Set
|
||||
<output id="neighbourSizeSliderOutput">6</output><br/>
|
||||
<input type="range" min="1" max="100" value="6" step="1" oninput="d3.select('#neighbourSizeSliderOutput').text(value); NEIGHBOUR_SIZE=value;">
|
||||
</label>
|
||||
<br/>
|
||||
<label title="SampleSize">
|
||||
Sample Set
|
||||
<output id="sampleSizeSliderOutput">3</output><br/>
|
||||
<input type="range" min="1" max="100" value="3" step="1" oninput="d3.select('#sampleSizeSliderOutput').text(value); SAMPLE_SIZE=value;">
|
||||
</label>
|
||||
</div>
|
||||
<input class="noParameters" type="radio" name="algorithm" onclick="d3.select('#startSimulation').on('click', startLinkSimulation)">Link
|
||||
force in D3<br>
|
||||
<input class="noParameters" type="radio" name="algorithm" onclick="d3.select('#startSimulation').on('click', startBarnesHutSimulation)">Barnes-Hut<br>
|
||||
<input id="tSNEButton" type="radio" name="algorithm" onclick="d3.select('#startSimulation').on('click', starttSNE)">t-SNE<br>
|
||||
<div id="tSNEParameters" class="parameters" style="display:none">
|
||||
<label title="Perplexity">
|
||||
Perplexity
|
||||
<output id="perplexitySliderOutput">30</output><br/>
|
||||
<input type="range" min="1" max="500" value="30" step="1" oninput="d3.select('#perplexitySliderOutput').text(value); PERPLEXITY=value;">
|
||||
</label>
|
||||
<br/>
|
||||
<label title="LearningRate">
|
||||
Learning Rate
|
||||
<output id="learningRateSliderOutput">10</output><br/>
|
||||
<input type="range" min="1" max="500" value="10" step="1" oninput="d3.select('#learningRateSliderOutput').text(value); LEARNING_RATE=value;">
|
||||
</label>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="left">
|
||||
<p>Select distance function:</p>
|
||||
<div id="distance">
|
||||
<input type="radio" name="distance" onclick="distanceFunction=calculateDistance"> General<br>
|
||||
<input type="radio" name="distance" onclick="distanceFunction=calculateEuclideanDistance"> Euclidean<br>
|
||||
<input type="radio" name="distance" onclick="distanceFunction=calculateManhattanDistance"> Manhattan<br>
|
||||
<input type="radio" name="distance" onclick="distanceFunction=calculateJaccardDissimilarity"> Jaccard<br>
|
||||
<input type="radio" name="distance" onclick="distanceFunction=calculateDiceDissimilarity"> Dice<br>
|
||||
<input type="radio" name="distance" onclick="distanceFunction=calculateCosineSimilarity"> Cosine<br>
|
||||
<input type="radio" name="distance" onclick="distanceFunction=calculateDistancePoker"> Poker Hands<br>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</svg>
|
||||
</body>
|
||||
|
||||
<!-- Load the files and libraries used. -->
|
||||
<script src="js/lib/d3.v4.min.js"></script>
|
||||
<script src="js/lib/papaparse.js"></script>
|
||||
<script src="js/lib/jquery-3.1.1.js"></script>
|
||||
<script src="js/lib/intercom.js"></script>
|
||||
<script src="../build/d3-neighbour-sampling.js"></script>
|
||||
<script src="js/src/neighbourSampling-papaparsing-nist-images.js"></script>
|
||||
<script src="js/distances/distancePokerHands.js"></script>
|
||||
<script src="js/distances/distance.js"></script>
|
||||
<script src="js/distances/euclideanDistance.js"></script>
|
||||
<script src="js/distances/euclideanDistanceInTSNE.js"></script>
|
||||
<script src="js/distances/manhattanDistance.js"></script>
|
||||
<script src="js/distances/jaccardDissimilarity.js"></script>
|
||||
<script src="js/distances/diceDissimilarity.js"></script>
|
||||
<script src="js/distances/cosineSimilarity.js"></script>
|
||||
<script src="js/distances/normalization.js"></script>
|
||||
<script src="js/distances/numeric.js"></script>
|
||||
|
||||
|
||||
<script>
|
||||
$(document).ready(function () {
|
||||
$("#csv-file").change(function (d) {
|
||||
parseFile(d);
|
||||
$("#color_attr option").remove();
|
||||
});
|
||||
|
||||
$("#tSNEButton").click(function () {
|
||||
$(".parameters").hide();
|
||||
$("#tSNEParameters").show();
|
||||
});
|
||||
|
||||
$("#NSButton").click(function () {
|
||||
$(".parameters").hide();
|
||||
$("#NSParameters").show();
|
||||
});
|
||||
|
||||
$("#HLButton").click(function () {
|
||||
$(".parameters").hide();
|
||||
$("#HLParameters").show();
|
||||
if ($("#PButton").is(":checked")) {
|
||||
$("#numPivots").show();
|
||||
}
|
||||
});
|
||||
|
||||
$("#BFButton").click(function () {
|
||||
$("#numPivots").hide();
|
||||
});
|
||||
|
||||
$("#PButton").click(function () {
|
||||
$("#numPivots").show();
|
||||
});
|
||||
|
||||
$(".noParameters").click(function () {
|
||||
$(".parameters").hide();
|
||||
});
|
||||
|
||||
});
|
||||
|
||||
</script>
|
||||
|
||||
</html>
|
||||
Reference in New Issue
Block a user