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

64 lines
1.7 KiB
Java

"use strict";
var _ = require("../lodash");
module.exports = {
longestPath: longestPath,
slack: slack
};
/*
* Initializes ranks for the input graph using the longest path algorithm. This
* algorithm scales well and is fast in practice, it yields rather poor
* solutions. Nodes are pushed to the lowest layer possible, leaving the bottom
* ranks wide and leaving edges longer than necessary. However, due to its
* speed, this algorithm is good for getting an initial ranking that can be fed
* into other algorithms.
*
* This algorithm does not normalize layers because it will be used by other
* algorithms in most cases. If using this algorithm directly, be sure to
* run normalize at the end.
*
* Pre-conditions:
*
* 1. Input graph is a DAG.
* 2. Input graph node labels can be assigned properties.
*
* Post-conditions:
*
* 1. Each node will be assign an (unnormalized) "rank" property.
*/
function longestPath(g) {
var visited = {};
function dfs(v) {
var label = g.node(v);
if (_.has(visited, v)) {
return label.rank;
}
visited[v] = true;
var rank = _.min(_.map(g.outEdges(v), function(e) {
return dfs(e.w) - g.edge(e).minlen;
}));
if (rank === Number.POSITIVE_INFINITY || // return value of _.map([]) for Lodash 3
rank === undefined || // return value of _.map([]) for Lodash 4
rank === null) { // return value of _.map([null])
rank = 0;
}
return (label.rank = rank);
}
_.forEach(g.sources(), dfs);
}
/*
* Returns the amount of slack for the given edge. The slack is defined as the
* difference between the length of the edge and its minimum length.
*/
function slack(g, e) {
return g.node(e.w).rank - g.node(e.v).rank - g.edge(e).minlen;
}