08-27-周三_17-09-29

node_modules/dagre-layout/lib/rank/util.js

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+import _ from 'lodash'
+
+/*
+ * 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.
+ */
+export function longestPath (g) {
+  const visited = {}
+
+  function dfs (v) {
+    const label = g.node(v)
+    if (_.has(visited, v)) {
+      return label.rank
+    }
+    visited[v] = true
+
+    const rank = _.min(_.map(g.outEdges(v), function (e) {
+      return dfs(e.w) - g.edge(e).minlen
+    })) || 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.
+ */
+export function slack (g, e) {
+  return g.node(e.w).rank - g.node(e.v).rank - g.edge(e).minlen
+}
+
+export default {
+  longestPath: longestPath,
+  slack: slack
+}