| /** |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you under the Apache License, Version 2.0 (the |
| * "License"); you may not use this file except in compliance |
| * with the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| * |
| */ |
| package org.apache.hadoop.tools.rumen; |
| |
| import java.util.Arrays; |
| import java.util.List; |
| import java.util.Random; |
| |
| /** |
| * An instance of this class generates random values that confirm to the |
| * embedded {@link LoggedDiscreteCDF} . The discrete CDF is a pointwise |
| * approximation of the "real" CDF. We therefore have a choice of interpolation |
| * rules. |
| * |
| * A concrete subclass of this abstract class will implement valueAt(double) |
| * using a class-dependent interpolation rule. |
| * |
| */ |
| public abstract class CDFRandomGenerator { |
| final double[] rankings; |
| final long[] values; |
| |
| final Random random; |
| |
| CDFRandomGenerator(LoggedDiscreteCDF cdf) { |
| this(cdf, new Random()); |
| } |
| |
| CDFRandomGenerator(LoggedDiscreteCDF cdf, long seed) { |
| this(cdf, new Random(seed)); |
| } |
| |
| private CDFRandomGenerator(LoggedDiscreteCDF cdf, Random random) { |
| this.random = random; |
| rankings = new double[cdf.getRankings().size() + 2]; |
| values = new long[cdf.getRankings().size() + 2]; |
| initializeTables(cdf); |
| } |
| |
| protected final void initializeTables(LoggedDiscreteCDF cdf) { |
| rankings[0] = 0.0; |
| values[0] = cdf.getMinimum(); |
| rankings[rankings.length - 1] = 1.0; |
| values[rankings.length - 1] = cdf.getMaximum(); |
| |
| List<LoggedSingleRelativeRanking> subjects = cdf.getRankings(); |
| |
| for (int i = 0; i < subjects.size(); ++i) { |
| rankings[i + 1] = subjects.get(i).getRelativeRanking(); |
| values[i + 1] = subjects.get(i).getDatum(); |
| } |
| } |
| |
| protected int floorIndex(double probe) { |
| int result = Arrays.binarySearch(rankings, probe); |
| |
| return Math.abs(result + 1) - 1; |
| } |
| |
| protected double getRankingAt(int index) { |
| return rankings[index]; |
| } |
| |
| protected long getDatumAt(int index) { |
| return values[index]; |
| } |
| |
| public long randomValue() { |
| return valueAt(random.nextDouble()); |
| } |
| |
| public abstract long valueAt(double probability); |
| } |