235 lines
6.5 KiB
Java
235 lines
6.5 KiB
Java
"use strict";
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var _ = require("../lodash");
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var feasibleTree = require("./feasible-tree");
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var slack = require("./util").slack;
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var initRank = require("./util").longestPath;
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var preorder = require("../graphlib").alg.preorder;
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var postorder = require("../graphlib").alg.postorder;
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var simplify = require("../util").simplify;
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module.exports = networkSimplex;
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// Expose some internals for testing purposes
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networkSimplex.initLowLimValues = initLowLimValues;
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networkSimplex.initCutValues = initCutValues;
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networkSimplex.calcCutValue = calcCutValue;
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networkSimplex.leaveEdge = leaveEdge;
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networkSimplex.enterEdge = enterEdge;
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networkSimplex.exchangeEdges = exchangeEdges;
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/*
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* The network simplex algorithm assigns ranks to each node in the input graph
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* and iteratively improves the ranking to reduce the length of edges.
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*
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* Preconditions:
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*
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* 1. The input graph must be a DAG.
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* 2. All nodes in the graph must have an object value.
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* 3. All edges in the graph must have "minlen" and "weight" attributes.
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*
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* Postconditions:
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*
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* 1. All nodes in the graph will have an assigned "rank" attribute that has
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* been optimized by the network simplex algorithm. Ranks start at 0.
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*
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*
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* A rough sketch of the algorithm is as follows:
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*
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* 1. Assign initial ranks to each node. We use the longest path algorithm,
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* which assigns ranks to the lowest position possible. In general this
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* leads to very wide bottom ranks and unnecessarily long edges.
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* 2. Construct a feasible tight tree. A tight tree is one such that all
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* edges in the tree have no slack (difference between length of edge
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* and minlen for the edge). This by itself greatly improves the assigned
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* rankings by shorting edges.
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* 3. Iteratively find edges that have negative cut values. Generally a
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* negative cut value indicates that the edge could be removed and a new
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* tree edge could be added to produce a more compact graph.
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*
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* Much of the algorithms here are derived from Gansner, et al., "A Technique
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* for Drawing Directed Graphs." The structure of the file roughly follows the
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* structure of the overall algorithm.
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*/
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function networkSimplex(g) {
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g = simplify(g);
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initRank(g);
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var t = feasibleTree(g);
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initLowLimValues(t);
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initCutValues(t, g);
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var e, f;
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while ((e = leaveEdge(t))) {
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f = enterEdge(t, g, e);
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exchangeEdges(t, g, e, f);
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}
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}
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/*
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* Initializes cut values for all edges in the tree.
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*/
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function initCutValues(t, g) {
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var vs = postorder(t, t.nodes());
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vs = vs.slice(0, vs.length - 1);
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_.forEach(vs, function(v) {
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assignCutValue(t, g, v);
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});
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}
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function assignCutValue(t, g, child) {
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var childLab = t.node(child);
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var parent = childLab.parent;
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t.edge(child, parent).cutvalue = calcCutValue(t, g, child);
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}
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/*
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* Given the tight tree, its graph, and a child in the graph calculate and
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* return the cut value for the edge between the child and its parent.
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*/
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function calcCutValue(t, g, child) {
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var childLab = t.node(child);
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var parent = childLab.parent;
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// True if the child is on the tail end of the edge in the directed graph
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var childIsTail = true;
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// The graph's view of the tree edge we're inspecting
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var graphEdge = g.edge(child, parent);
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// The accumulated cut value for the edge between this node and its parent
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var cutValue = 0;
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if (!graphEdge) {
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childIsTail = false;
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graphEdge = g.edge(parent, child);
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}
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cutValue = graphEdge.weight;
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_.forEach(g.nodeEdges(child), function(e) {
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var isOutEdge = e.v === child,
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other = isOutEdge ? e.w : e.v;
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if (other !== parent) {
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var pointsToHead = isOutEdge === childIsTail,
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otherWeight = g.edge(e).weight;
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cutValue += pointsToHead ? otherWeight : -otherWeight;
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if (isTreeEdge(t, child, other)) {
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var otherCutValue = t.edge(child, other).cutvalue;
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cutValue += pointsToHead ? -otherCutValue : otherCutValue;
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}
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}
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});
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return cutValue;
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}
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function initLowLimValues(tree, root) {
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if (arguments.length < 2) {
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root = tree.nodes()[0];
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}
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dfsAssignLowLim(tree, {}, 1, root);
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}
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function dfsAssignLowLim(tree, visited, nextLim, v, parent) {
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var low = nextLim;
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var label = tree.node(v);
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visited[v] = true;
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_.forEach(tree.neighbors(v), function(w) {
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if (!_.has(visited, w)) {
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nextLim = dfsAssignLowLim(tree, visited, nextLim, w, v);
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}
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});
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label.low = low;
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label.lim = nextLim++;
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if (parent) {
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label.parent = parent;
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} else {
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// TODO should be able to remove this when we incrementally update low lim
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delete label.parent;
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}
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return nextLim;
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}
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function leaveEdge(tree) {
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return _.find(tree.edges(), function(e) {
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return tree.edge(e).cutvalue < 0;
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});
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}
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function enterEdge(t, g, edge) {
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var v = edge.v;
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var w = edge.w;
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// For the rest of this function we assume that v is the tail and w is the
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// head, so if we don't have this edge in the graph we should flip it to
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// match the correct orientation.
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if (!g.hasEdge(v, w)) {
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v = edge.w;
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w = edge.v;
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}
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var vLabel = t.node(v);
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var wLabel = t.node(w);
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var tailLabel = vLabel;
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var flip = false;
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// If the root is in the tail of the edge then we need to flip the logic that
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// checks for the head and tail nodes in the candidates function below.
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if (vLabel.lim > wLabel.lim) {
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tailLabel = wLabel;
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flip = true;
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}
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var candidates = _.filter(g.edges(), function(edge) {
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return flip === isDescendant(t, t.node(edge.v), tailLabel) &&
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flip !== isDescendant(t, t.node(edge.w), tailLabel);
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});
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return _.minBy(candidates, function(edge) { return slack(g, edge); });
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}
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function exchangeEdges(t, g, e, f) {
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var v = e.v;
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var w = e.w;
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t.removeEdge(v, w);
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t.setEdge(f.v, f.w, {});
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initLowLimValues(t);
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initCutValues(t, g);
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updateRanks(t, g);
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}
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function updateRanks(t, g) {
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var root = _.find(t.nodes(), function(v) { return !g.node(v).parent; });
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var vs = preorder(t, root);
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vs = vs.slice(1);
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_.forEach(vs, function(v) {
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var parent = t.node(v).parent,
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edge = g.edge(v, parent),
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flipped = false;
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if (!edge) {
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edge = g.edge(parent, v);
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flipped = true;
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}
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g.node(v).rank = g.node(parent).rank + (flipped ? edge.minlen : -edge.minlen);
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});
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}
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/*
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* Returns true if the edge is in the tree.
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*/
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function isTreeEdge(tree, u, v) {
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return tree.hasEdge(u, v);
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}
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/*
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* Returns true if the specified node is descendant of the root node per the
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* assigned low and lim attributes in the tree.
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*/
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function isDescendant(tree, vLabel, rootLabel) {
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return rootLabel.low <= vLabel.lim && vLabel.lim <= rootLabel.lim;
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}
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