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Code Issues 3 Releases 4 Activity

Change velocity-difference threshold calculation method and misc small non-functional changes (PROPER)

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This commit is contained in:
Pitchaya Boonsarngsuk
2018-01-24 08:55:49 +00:00
parent df652ffec6
commit 6b53b3301d
7 changed files with 95 additions and 279 deletions
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1
examples/js/src/neighbourSampling-papaparsing/linkForce.js
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@@ -27,6 +27,7 @@ function startLinkSimulation() {
simulation
.alphaDecay(1 - Math.pow(0.001, 1 / ITERATIONS))
//.velocityDecay(0.8)
.force(forceName)
// The distance function that will be used to calculate distances
// between nodes.

2
examples/js/src/neighbourSampling-papaparsing/neighbourSampling.js
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@@ -20,7 +20,7 @@ function startNeighbourSamplingSimulation() {
.distance(function (s, t) {
return distanceFunction(s, t, props, norm);
})
.stableVelocity(1.2)
.stableVelocity(0.004)
.stableVeloHandler( function(){simulation.stop(); ended();} )
);
// Restart the simulation.

13
src/hybridSimulation.js
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@@ -39,7 +39,7 @@ export default function (nodes, config) {
.sampleSize(sampleSize)
.distanceRange(distanceRange)
.distance(distanceFn)
.stableVelocity(60)
.stableVelocity(0.004)
.stableVeloHandler(function(){sampleSimulation.stop(); ended();})
)
.alpha(1).restart();
@@ -52,14 +52,11 @@ export default function (nodes, config) {
event.call("startFull");
console.log("Ended sample simulation");
alert('About to interpolate');
interpBruteForce(sample, remainder, distanceFn);
/*
if (PIVOTS) {
interpolationPivots(sample, remainder, sampleSubSet, NUMPIVOTS, distance);
interpolationPivots(sample, remainder, NUMPIVOTS, distanceFn);
} else {
interpBruteForce(sample, remainder, sampleSubSet, distance);
interpBruteForce(sample, remainder, distanceFn);
}
*/
event.call("fullTick");
alert('About to Full run');
if (FULL_ITERATIONS==0) {
@@ -77,7 +74,7 @@ export default function (nodes, config) {
.sampleSize(FullsampleSize)
.distanceRange(FulldistanceRange)
.distance(distanceFn)
.stableVelocity(60)
.stableVelocity(0.004)
.stableVeloHandler(function(){fullSimulation.stop(); event.call("end");})
)
.on("tick", function () {
@@ -152,5 +149,5 @@ export default function (nodes, config) {
}
function readConf(config, prop, def){
return config.hasOwnProperty(prop) ? config.prop : def;
return config.hasOwnProperty(prop) ? config[prop] : def;
}

3
src/interpolation/interpBruteForce.js
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@@ -7,8 +7,7 @@ export default function(sampleSet, remainderSet, distanceFn) {
let sampleSubset = takeSampleFrom(sampleSet, Math.sqrt(sampleSet.length)).sample;
for (let node of remainderSet) {
let nearestSample = undefined,
minDist = undefined,
let nearestSample, minDist,
sampleSubsetDistanceCache = [];
for (let sample of sampleSet) {

7
src/interpolation/interpCommon.js
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@@ -48,11 +48,12 @@ export function placeNearToNearestNeighbour(node, nearNeighbour, radius, sampleS
node.x = newPoint.x;
node.y = newPoint.y;
let sumForces; // Common temp variables, avoid GC
for (let i = 0; i < 20; i++) {
let forces = sumForcesToSample(node, sampleSubset, realDistances);
sumForces = sumForcesToSample(node, sampleSubset, realDistances);
//console.log(forces);
node.x += forces.x*0.5;
node.y += forces.y*0.5;
node.x += sumForces.x*0.5;
node.y += sumForces.y*0.5;
}
}

325
src/interpolation/interpolationPivots.js
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@@ -1,287 +1,98 @@
export default function(sampleSet, remainderSet, interpSubset, nPivots, distanceFunction) {
var distance = distanceFunction;
import {pointOnCircle, takeSampleFrom} from "./helpers";
import {placeNearToNearestNeighbour} from "./interpCommon";
export default function(sampleSet, remainderSet, numPivots, distanceFn) {
// Pivot based parent finding
let numBuckets = Math.floor(Math.sqrt(sampleSet.length));
let pivots = takeSampleFrom(sampleSet, numPivots);
console.log("Pivots", pivots);
// Common temporary variables
let i, j, pivot, sample, bucketWidth; // Temp var, declared seperately to avoid GC
var numBuckets = Math.floor(Math.sqrt(sampleSet.length)),
numPivots = nPivots,
parents = [],
maxDists = [],
bucketWidths = [],
pivotsBuckets = [];
let pivotsBuckets = []; // [ For each Pivot:[For each bucket:[each point in bucket]] ]
console.log("Parents, pivots=", numPivots);
var pivots = createRandomSample(sampleSet.concat(remainderSet), sampleSet.length, numPivots);
for (var i = 0; i < numPivots; i++) {
for (i = 0; i < numPivots; i++) {
pivotsBuckets[i] = [];
for (var j = 0; j < numBuckets; j++) {
for (j = 0; j < numBuckets; j++) {
pivotsBuckets[i][j] = [];
}
}
// Pre-processing
var fullDists = []
for (var i = 0; i < sampleSet.length; i++) {
fullDists[i] = [];
}
// Pre-calculate distance between each sample to each pivot
let distCache = [], // [ For each Sample:[For each Pivot: distance] ]
bucketWidths = []; // [ For each Pivot: width of each bucket ]
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, props, norm);
// console.log(dist, c1, c2);
if (dist > maxDist) {
maxDist = dist;
}
fullDists[i][j] = dist;
for (i = 0; i < sampleSet.length; i++)
distCache[i] = [];
for (j = 0; j < numPivots; j++) {
pivot = pivots[j],
maxDist = -1;
for (i = 0; i < sampleSet.length; i++) {
sample = sampleSet[i];
if (pivot !== sample) {
distCache[i][j] = distanceFn(pivot, sample);
if (distCache[i][j] > maxDist)
maxDist = distCache[i][j];
} else {
fullDists[i][j] = 0.0001;
distCache[i][j] = 0;
}
}
maxDists.push(maxDist);
bucketWidths.push(maxDist / numBuckets);
}
// console.log(fullDists);
// console.log(distCaches);
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]);
// Put samples (pivot included) into buckets
for (j = 0; j < numPivots; j++) {
bucketWidth = bucketWidths[j];
for (i = 0; i < sampleSet.length; i++) {
sample = sampleSet[i];
pivotsBuckets[j][Math.floor(distCache[i][j] / bucketWidth)].push(sample);
}
}
for (var i = 0; i < remainderSet.length; i++) {
var node = remainderSet[i],
minNode = sampleSet[0],
minDist = 0,
sampleCache = [];
//Plot each of the remainder nodes
for (let node of remainderSet) {
let sampleSubsetDistanceCache = [],
sampleSubset = takeSampleFrom(sampleSet, Math.sqrt(sampleSet.length)).sample;
// Pivot based parent search
for (let p = 0; p < numPivots; p++) {
let pivot = pivots[p];
let bucketWidth = bucketWidths[p];
var node = remainderSet[i];
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, props, norm);
var 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, props, norm);
if (dist <= clDist) {
clDist = dist;
minNode = bucketContents[w];
}
}
let dist = distanceFn(node, pivot);
let index = sampleSubset.indexOf(pivot);
if (index !== -1)
sampleSubsetDistanceCache[index] = dist;
let bucketNumber = Math.floor(dist / bucketWidth);
if (bucketNumber >= numBuckets) {
bucketNumber = numBuckets - 1;
} else if (bucketNumber < 0) { // Should never be negative anyway
bucketNumber = 0;
}
let clDist, minNode;
for (let candidateNode of pivotsBuckets[p][bucketNumber]) {
dist = distanceFn(candidateNode, node);
if (candidateNode <= clDist) {
clDist = candidateNode;
minNode = bucketContents[w];
}
}
}
for (var k = 0; k < interpSubset.length; k++) {
sampleCache[k] = distance(node, interpSubset[k], props, norm);
for (let k = 0; k < sampleSubset.length; k++) {
if (sampleSubsetDistanceCache[k] !== undefined)
sampleSubsetDistanceCache[k] = distanceFn(node, sampleSubset[k]);
}
var radius = distance(node, minNode, props, norm);
placeNearToNearestNeighbour(node, minNode, interpSubset, sampleCache, radius);
let radius = distanceFn(node, minNode);
placeNearToNearestNeighbour(node, minNode, radius, sampleSubset, sampleSubsetDistanceCache);
}
}
function placeNearToNearestNeighbour(node, minNode, sample, sampleCache, radius) {
var
dist0 = 0.0,
dist90 = 0.0,
dist180 = 0.0,
dist270 = 0.0,
lowBound = 0.0,
highBound = 0.0;
dist0 = sumDistToSample(node, centerPoint(0, radius, minNode.x, minNode.y), sample, sampleCache);
dist90 = sumDistToSample(node, centerPoint(90, radius, minNode.x, minNode.y), sample, sampleCache);
dist180 = sumDistToSample(node, centerPoint(180, radius, minNode.x, minNode.y), sample, sampleCache);
dist270 = sumDistToSample(node, centerPoint(270, radius, minNode.x, minNode.y), sample, sampleCache);
// console.log(dist0, dist90, dist180, dist270);
// Determine the closest quadrant
if (dist0 == dist180) {
if (dist90 > dist270)
lowBound = highBound = 270;
else
lowBound = highBound = 90;
} else if (dist90 == dist270) {
if (dist0 > dist180)
lowBound = highBound = 180;
else
lowBound = highBound = 0;
} else if (dist0 > dist180) {
if (dist90 > dist270) {
lowBound = 180;
highBound = 270;
} else {
lowBound = 90;
highBound = 180;
}
} else {
if (dist90 > dist270) {
lowBound = 270;
highBound = 360;
} else {
lowBound = 0;
highBound = 90;
}
}
var angle = binarySearch(lowBound, highBound, minNode.x, minNode.y, radius, node, sample, sampleCache);
var newPoint = centerPoint(angle, radius, minNode.x, minNode.y);
// console.log(newPoint);
node.x = newPoint.x;
node.y = newPoint.y;
// for (var i = 0; i < 20; i++) {
// var forces = sumForcesToSample(node, sample, sampleCache);
// // console.log(forces);
// node.x += forces.x;
// node.y += forces.y;
// }
}
function centerPoint(angle, radius, posX, posY) {
var x = posX + Math.cos(toRadians(angle) * radius);
var y = posY + Math.sin(toRadians(angle) * radius);
return {
x: x,
y: y
};
}
function toRadians(degrees) {
return degrees * (Math.PI / 180);
}
function sumDistToSample(node, point, sample, sampleCache) {
var total = 0.0;
// console.log(total, sample);
for (var i = 0; i < sample.length; i++) {
var s = sample[i];
var realDist = Math.hypot(s.x - point.x, s.y - point.y);
var desDist = sampleCache[i];
total += Math.abs(realDist - desDist);
}
return total;
}
function sumForcesToSample(node, sample, sampleCache) {
var x = 0,
y = 0,
// len = 0,
dist = 0,
force,
SPRING_FORCE = 0.7;
for (var i = 0, unitX, unitY; i < sample.length; i++) {
var s = sample[i];
if (s !== node) {
unitX = s.x - node.x;
unitY = s.y - node.y;
// Normalize coordinates
len = Math.sqrt(unitX * unitX + unitY * unitY);
unitX /= len;
unitY /= len;
console.log(unitX, unitY);
var realDist = Math.sqrt(unitX * unitX + unitY * unitY);
var desDist = sampleCache[i];
dist += realDist - desDist;
force = (SPRING_FORCE * dist);
x += unitX * force;
y += unitY * force;
}
x *= (1.0 / sample.length);
y *= (1.0 / sample.length);
return {
x: x,
y: y
};
}
}
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;
}
function binarySearch(lb, hb, x, y, r, node, sample, sampleCache) {
while (lb <= hb) {
var mid = Math.round((lb + hb) / 2);
if ((mid === lb) || (mid === hb)) {
if (sumDistToSample(node, centerPoint(lb, r, x, y), sample, sampleCache) >=
sumDistToSample(node, centerPoint(hb, r, x, y), sample, sampleCache)) {
return hb;
} else {
return lb;
}
} else {
var distMidLeft = sumDistToSample(node, centerPoint(mid + 1, r, x, y), sample, sampleCache);
var distMidRight = sumDistToSample(node, centerPoint(mid - 1, r, x, y), sample, sampleCache);
var distMid = sumDistToSample(node, centerPoint(mid, r, x, y), sample, sampleCache);
if (distMid > distMidLeft) {
lb = mid + 1;
} else if (distMid > distMidRight) {
hb = mid - 1;
} else {
return mid;
}
}
}
return -1;
}

23
src/neighbourSamplingDistance.js
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@@ -41,7 +41,11 @@ export default function () {
* particle simulations.
*/
function force(alpha) {
velocity = 0;
let velocityDiff = 0;
for (let node of nodes) {
node.oldvx = node.vx;
node.oldvy = node.vy;
}
for (let i = 0, n = nodes.length; i < n; ++i) {
// Randomize the samples for every node.
samples[i] = randomizeSample(i);
@@ -57,15 +61,19 @@ export default function () {
// for each node.
findNewNeighbours(i);
}
velocity /= nodes.length*(neighbours.length+samples.length)*alpha;
// Now total velocity changes per link, alpha not considered
for (let node of nodes) {
velocityDiff += Math.abs(node.oldvx - node.vx) + Math.abs(node.oldvy - node.vy);
delete node.oldvx;
delete node.oldvy;
}
velocityDiff /= nodes.length*(neighbourSize+sampleSize);
// Now total velocity changes per link, alpha considered
// TODO per property too
stableVelocity = 0;
if(Math.abs(velocity)<stableVelocity && stableVeloHandler!== null){
console.log("Neighbour sampling is now", velocity, ", calling stableVeloHandler().")
if(stableVeloHandler!==null && velocityDiff<stableVelocity){
console.log("Neighbour sampling is now", velocityDiff, ", calling stableVeloHandler().")
stableVeloHandler();
}
//else console.log(velocity);
else console.log(velocityDiff);
}
/**
@@ -85,7 +93,6 @@ export default function () {
l = Math.sqrt(x * x + y * y);
l = (l - dist) / l * alpha;
x *= l, y *= l;
velocity += Math.abs(x) + Math.abs(y);
// Set the calculated velocites for both nodes.
target.vx -= x*0.5;
target.vy -= y*0.5;