package org.arabidopsis.ahocorasick; import java.util.HashSet; import java.util.Set; /** * A state represents an element in the Aho-Corasick tree. */ class State<T> { // Arbitrarily chosen constant. If this state ends up getting // deeper than THRESHOLD_TO_USE_SPARSE, then we switch over to a // sparse edge representation. I did a few tests, and there's a // local minima here. We may want to choose a more sophisticated // strategy. private static final int THRESHOLD_TO_USE_SPARSE = 3; private int depth; private EdgeList edgeList; private State fail; private Set<Object> outputs; public State(int depth) { this.depth = depth; if (depth > THRESHOLD_TO_USE_SPARSE) this.edgeList = new SparseEdgeList(); else this.edgeList = new DenseEdgeList(); this.fail = null; this.outputs = new HashSet<Object>(); } public State extend(char b) { if (this.edgeList.get(b) != null) return this.edgeList.get(b); State nextState = new State(this.depth + 1); this.edgeList.put(b, nextState); return nextState; } public State extendAll(char[] chars) { State state = this; for (int i = 0; i < chars.length; i++) { if (state.edgeList.get(chars[i]) != null) state = state.edgeList.get(chars[i]); else state = state.extend(chars[i]); } return state; } /** * Returns the size of the tree rooted at this State. Note: do not call this if there are loops * in the edgelist graph, such as those introduced by AhoCorasick.prepare(). */ public int size() { char[] keys = edgeList.keys(); int result = 1; for (int i = 0; i < keys.length; i++) result += edgeList.get(keys[i]).size(); return result; } public State get(char b) { return this.edgeList.get(b); } public void put(char b, State s) { this.edgeList.put(b, s); } public char[] keys() { return this.edgeList.keys(); } public State getFail() { return this.fail; } public void setFail(State f) { this.fail = f; } public void addOutput(Object o) { this.outputs.add(o); } public Set<Object> getOutputs() { return this.outputs; } }