NuclearDispersionSystem/ant-design-vue-jeecg/node_modules/dagre/lib/rank/network-simplex.js
2023-09-14 14:47:11 +08:00

235 lines
6.5 KiB
Java

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