Java tutorial
/* LICENSE Copyright (c) 2013-2016, Jesse Hostetler (jessehostetler@gmail.com) All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ /** * */ package edu.oregonstate.eecs.mcplan.ml; import java.util.ArrayDeque; import java.util.ArrayList; import java.util.Arrays; import java.util.Comparator; import java.util.Deque; import java.util.HashMap; import java.util.List; import java.util.Map; import java.util.PriorityQueue; import weka.core.Attribute; import weka.core.DenseInstance; import weka.core.Instance; import weka.core.Instances; import edu.oregonstate.eecs.mcplan.FactoredRepresentation; import edu.oregonstate.eecs.mcplan.VirtualConstructor; import edu.oregonstate.eecs.mcplan.search.ActionNode; import edu.oregonstate.eecs.mcplan.search.GameTree; import edu.oregonstate.eecs.mcplan.search.GameTreeVisitor; import edu.oregonstate.eecs.mcplan.search.StateNode; import edu.oregonstate.eecs.mcplan.util.Fn; import edu.oregonstate.eecs.mcplan.util.Tuple.Tuple2; /** * @author jhostetler * */ public abstract class GameTreeStateSimilarityDataset<S extends FactoredRepresentation<?>, A extends VirtualConstructor<A>> implements Runnable { private class Visitor implements GameTreeVisitor<S, A> { public final HashMap<List<ActionNode<S, A>>, List<StateNode<S, A>>> xs = new HashMap<List<ActionNode<S, A>>, List<StateNode<S, A>>>(); private final Deque<ActionNode<S, A>> ahist_ = new ArrayDeque<ActionNode<S, A>>(); @Override public void visit(final StateNode<S, A> s) { for (final ActionNode<S, A> a : Fn.in(s.successors())) { ahist_.push(a); a.accept(this); ahist_.pop(); } } @Override public void visit(final ActionNode<S, A> a) { final List<ActionNode<S, A>> key; if (use_action_context_) { key = new ArrayList<ActionNode<S, A>>(ahist_); } else { key = null; } List<StateNode<S, A>> values = xs.get(key); if (values == null) { values = new ArrayList<StateNode<S, A>>(); xs.put(key, values); } for (final StateNode<S, A> s : Fn.in(a.successors())) { if (s.successors().hasNext()) { // If not leaf node values.add(s); } } // System.out.println( "***** values.size() = " + values.size() ); for (final StateNode<S, A> s : Fn.in(a.successors())) { s.accept(this); } } } public final int label_index; private final GameTree<S, A> tree_; private final ArrayList<Attribute> attributes_; private final int player_; private final int min_samples_; private final int max_instances_; private final boolean use_action_context_; private final HashMap<List<ActionNode<S, A>>, Instances> xs_ = new HashMap<List<ActionNode<S, A>>, Instances>(); public GameTreeStateSimilarityDataset(final GameTree<S, A> tree, final ArrayList<Attribute> attributes, final int player, final int min_samples, final int max_instances, final boolean use_action_context) { tree_ = tree; attributes_ = attributes; player_ = player; min_samples_ = min_samples; max_instances_ = max_instances; label_index = attributes.size() - 1; use_action_context_ = use_action_context; } @Override public void run() { System.out.println("*** Extracting state nodes"); final Visitor visitor = new Visitor(); tree_.root().accept(visitor); // This extracts only the level-1 nodes. // TODO: Do this somewhere better. final HashMap<List<ActionNode<S, A>>, List<StateNode<S, A>>> tx = new HashMap<List<ActionNode<S, A>>, List<StateNode<S, A>>>(); final ArrayList<StateNode<S, A>> depth_1 = new ArrayList<StateNode<S, A>>(); for (final Map.Entry<List<ActionNode<S, A>>, List<StateNode<S, A>>> e : visitor.xs.entrySet()) { if (e.getKey() == null || e.getKey().size() != 1) { continue; } else { depth_1.addAll(e.getValue()); } } tx.put(null, depth_1); final Comparator<Instance> weight_comp = new Comparator<Instance>() { @Override public int compare(final Instance a, final Instance b) { return (int) Math.signum(a.weight() - b.weight()); } }; final int max_cap = max_instances_ + 1; final PriorityQueue<Instance> positive = new PriorityQueue<Instance>(max_cap, weight_comp); final PriorityQueue<Instance> negative = new PriorityQueue<Instance>(max_cap, weight_comp); System.out.println("*** Building Instances"); for (final Map.Entry<List<ActionNode<S, A>>, List<StateNode<S, A>>> e : tx.entrySet()) { System.out.println("***** key = " + e.getKey() + ", value.size() = " + e.getValue().size()); final String name = (e.getKey() != null ? e.getKey().toString() : "null"); final List<StateNode<S, A>> values = e.getValue(); final int[] num_instances = { 0, 0 }; int count = 0; for (int i = 0; i < values.size(); ++i) { for (int j = i + 1; j < values.size(); ++j) { if (count++ % 100 == 0) { System.out.println("***** instance " + (count - 1)); } final StateNode<S, A> s_i = values.get(i); final StateNode<S, A> s_j = values.get(j); if (s_i.n() < min_samples_ || s_j.n() < min_samples_) { System.out.println("! skipping under-sampled state pair"); continue; } final double[] phi_i = s_i.token.phi(); final double[] phi_j = s_j.token.phi(); assert (phi_i.length == phi_j.length); if (phi_i.length != attributes_.size() - 1) { System.out.println("! phi_i.length = " + phi_i.length); System.out.println("! attributes_.size() = " + attributes_.size()); } assert (phi_i.length == attributes_.size() - 1); // Feature vector is absolute difference of the two state // feature vectors. final double[] phi_labeled = new double[phi_i.length + 1]; for (int k = 0; k < phi_i.length; ++k) { phi_labeled[k] = Math.abs(phi_i[k] - phi_j[k]); } final Tuple2<Integer, Double> labeled = label(e.getKey(), player_, s_i, s_j); final int label = labeled._1; final double weight = labeled._2; final String label_string = Integer.toString(label); phi_labeled[label_index] = label; //attributes.get( label_index ).indexOfValue( label_string ); num_instances[label] += 1; final Instance instance = new DenseInstance(weight, phi_labeled); if (label == 0) { negative.add(instance); if (negative.size() >= max_cap) { negative.poll(); } } else { positive.add(instance); if (positive.size() >= max_cap) { positive.poll(); } } } // for j } // for i System.out.println("num_instances = " + Arrays.toString(num_instances)); final Instances x = new Instances(name, attributes_, negative.size() + positive.size()); x.setClassIndex(label_index); x.addAll(negative); x.addAll(positive); xs_.put(e.getKey(), x); } } public HashMap<List<ActionNode<S, A>>, Instances> getInstances() { return xs_; } public Instances getInstances(final List<ActionNode<S, A>> path) { return xs_.get(path); } public abstract Tuple2<Integer, Double> label(final List<ActionNode<S, A>> path, final int player, final StateNode<S, A> s1, final StateNode<S, A> s2); }