Separate a Link Force with optimization
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@@ -41,7 +41,8 @@ var nodes, // as in Data points
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fileName = "",
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selectedData,
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clickedIndex = -1,
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paused = false;
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paused = false,
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alreadyRanIterations;
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// Default parameters
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var MULTIPLIER = 50,
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@@ -119,10 +120,16 @@ function processData(data, error) {
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props.pop(); //Hide Iris index / last column from distance function
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//Put the nodes in random starting positions
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//TODO Change this back
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nodes.forEach(function (d) {
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d.x = 0;
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d.y = 0;
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});
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/*
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nodes.forEach(function (d) {
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d.x = (Math.random()-0.5) * 100000;
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d.y = (Math.random()-0.5) * 100000;
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});
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});*/
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addNodesToDOM(nodes);
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@@ -180,6 +187,8 @@ function addNodesToDOM(data) {
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}
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function ticked() {
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console.log("ticked");
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alreadyRanIterations++;
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// If rendering is selected, then draw at every iteration.
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if (rendering === true) {
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node // Each sub-circle in the SVG, update cx and cy
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@@ -194,9 +203,14 @@ function ticked() {
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if (springForce) {
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intercom.emit("passedData", simulation.force(forceName).distributionData());
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}
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if(alreadyRanIterations == ITERATIONS) {
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simulation.stop();
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ended();
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}
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}
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function ended() {
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console.log("ended");
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if (rendering !== true) { // Never drawn anything before? Now it's time.
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node
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.attr("cx", function (d) {
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@@ -1,40 +1,45 @@
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/**
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* Initialize the link force algorithm and start simulation.
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*/
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function startLinkSimulation() {
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console.log("startLinkSimulation")
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springForce = false;
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alreadyRanIterations = 0;
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simulation.stop();
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p1 = performance.now();
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let links = [];
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// Initialize link array.
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nodes = simulation.nodes();
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for (i = 0; i < nodes.length; i++) {
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for (j = 0; j < i; j++) {
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if (i !== j) {
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links.push({
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source: nodes[i],
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target: nodes[j],
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});
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}
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for (i = nodes.length-1; i >= 1; i--) {
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for (j = i-1; j >= 0; j--) {
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links.push({
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source: nodes[i],
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target: nodes[j],
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});
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}
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}
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// Add the links to the simulation.
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simulation.force(forceName, d3.forceLink().links(links));
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simulation
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.alphaDecay(1 - Math.pow(0.001, 1 / ITERATIONS))
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/* Add force
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* Please add the distance function before feeding the force
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* it to the simulation or adding links.
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*
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* On setting the distance fn and being initialized by the simulation, the
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* force will pre-calculate high-dimensional distances of every link and
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* store that as cache.
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* Adding distance fn before links means that the first pre-calculation will
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* calculate noting as there was no link.
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* The full pre-calculation will then occur once when the force is being
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* initialized by the simulation.
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*/
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simulation.force(forceName,
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d3.forceLinkOptimized()
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.distance(function (n) {
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return distanceFunction(n.source, n.target, props, norm);
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})
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.links(links)
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).alphaDecay(0)
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//.velocityDecay(0.8)
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.force(forceName)
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// The distance function that will be used to calculate distances
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// between nodes.
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.distance(function (n) {
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return distanceFunction(n.source, n.target, props, norm);
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})
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// Set the parameter for the algorithm (optional).
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// Restart the simulation.
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simulation.alpha(1).restart();
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.alpha(1)
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.restart();
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}
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36
index.js
36
index.js
@@ -1,28 +1,20 @@
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/*export {
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default as forceNeighbourSampling
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}
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/*
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export {default as forceNeighbourSampling}
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from "./src/neighbourSampling";
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export {
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default as forceNeighbourSamplingPre
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}
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from "./src/neighbourSamplingPre";*/
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export {
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default as forceNeighbourSamplingDistance
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}
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export {default as forceNeighbourSamplingPre}
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from "./src/neighbourSamplingPre";
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*/
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export {default as forceNeighbourSamplingDistance}
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from "./src/neighbourSamplingDistance";
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export {
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default as forceBarnesHut
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}
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export { default as forceBarnesHut}
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from "./src/barnesHut";
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export {
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default as tSNE
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}
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export { default as tSNE}
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from "./src/t-sne";
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export {
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default as forceLink
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}
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export { default as forceLinkOptimized}
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from "./src/link";
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export {
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default as hybridSimulation
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}
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export { default as hybridSimulation}
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from "./src/hybridSimulation";
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99
src/link.js
99
src/link.js
@@ -1,100 +1,53 @@
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import constant from "./constant";
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import jiggle from "./jiggle";
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import {map} from "d3-collection";
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import {getStress} from "./stress";
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/**
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* Extended link force algorithm to include the stress metric for
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* comparisons between the different algorithms.
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* Everything else is the same as in D3 force module.
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* Modified link force algorithm
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* - ignore alpha
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* - removed location prediction, and bias
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* - modified strength calculation
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* - removed other unused functions
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* Making it more suitable for the spring model.
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*/
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function index(d, i) {
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return i;
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}
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function find(nodeById, nodeId) {
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var node = nodeById.get(nodeId);
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if (!node) throw new Error("missing: " + nodeId);
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return node;
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}
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export default function(links) {
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var id = index,
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strength = defaultStrength,
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strengths,
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var dataSizeFactor,
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distance = constant(30),
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distances,
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distances = [],
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nodes,
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count,
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bias,
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iterations = 1;
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if (links == null) links = [];
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function defaultStrength(link) {
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return 1 / Math.min(count[link.source.index], count[link.target.index]);
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}
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function force(alpha) {
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function force() {
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for (var k = 0, n = links.length; k < iterations; ++k) { // Each iteration in a tick
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for (var i = 0, link, source, target, x, y, l, b; i < n; ++i) { //For each link
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for (var i = 0, link, source, target, x, y, l, b; i < n; ++i) { // For each link
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link = links[i];
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// jiggle so it wont divide / multiply by zero after this
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source = link.source;
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target = link.target;
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x = target.x + target.vx - source.x - source.vx || jiggle();
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y = target.y + target.vy - source.y - source.vy || jiggle();
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x = target.x - source.x || jiggle();
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y = target.y - source.y || jiggle();
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l = Math.sqrt(x * x + y * y);
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l = (l - distances[i]) / l * alpha * strengths[i];
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l = (l - distances[i]) / l * dataSizeFactor;
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x *= l, y *= l;
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target.vx -= x * (b = bias[i]);
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target.vy -= y * b;
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source.vx += x * (b = 1 - b);
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source.vy += y * b;
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target.vx -= x;
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target.vy -= y;
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source.vx += x;
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source.vy += y;
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}
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}
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}
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function initialize() {
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if (!nodes) return;
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var i,
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n = nodes.length,
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m = links.length,
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nodeById = map(nodes, id),
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link;
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for (i = 0, count = new Array(n); i < n; ++i) {
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count[i] = 0;
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}
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for (i = 0; i < m; ++i) {
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link = links[i];
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link.index = i;
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//if (typeof link.source !== "object") link.source = find(nodeById, link.source);
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//if (typeof link.target !== "object") link.target = find(nodeById, link.target);
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++count[link.source.index];
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++count[link.target.index];
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}
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for (i = 0, bias = new Array(m); i < m; ++i) {
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link = links[i];
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bias[i] = count[link.source.index] / (count[link.source.index] + count[link.target.index]);
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}
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strengths = new Array(m), initializeStrength();
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distances = new Array(m), initializeDistance();
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}
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function initializeStrength() {
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if (!nodes) return;
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for (var i = 0, n = links.length; i < n; ++i) {
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strengths[i] = +strength(links[i], i, links);
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}
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console.log("CUSTOM LINK FORCE");
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dataSizeFactor = 0.5/(nodes.length-1);
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initializeDistance();
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}
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function initializeDistance() {
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console.log("INIT DISTANCE", links.length);
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if (!nodes) return;
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for (var i = 0, n = links.length; i < n; ++i) {
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@@ -119,17 +72,9 @@ export default function(links) {
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return arguments.length ? (iterations = +_, force) : iterations;
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};
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force.strength = function(_) {
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return arguments.length ? (strength = typeof _ === "function" ? _ : constant(+_), initializeStrength(), force) : strength;
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};
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force.distance = function(_) {
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return arguments.length ? (distance = typeof _ === "function" ? _ : constant(+_), initializeDistance(), force) : distance;
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};
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force.stress = function() {
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return getStress(nodes, function(s,t){return distance({source: s, target: t});});
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}
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return force;
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}
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