DiscreteProbabilityCollectionSampler.java
- /*
- * 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.commons.rng.sampling;
- import java.util.List;
- import java.util.Map;
- import java.util.ArrayList;
- import org.apache.commons.rng.UniformRandomProvider;
- import org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler;
- import org.apache.commons.rng.sampling.distribution.SharedStateDiscreteSampler;
- /**
- * Sampling from a collection of items with user-defined
- * <a href="http://en.wikipedia.org/wiki/Probability_distribution#Discrete_probability_distribution">
- * probabilities</a>.
- * Note that if all unique items are assigned the same probability,
- * it is much more efficient to use {@link CollectionSampler}.
- *
- * <p>Sampling uses {@link UniformRandomProvider#nextDouble()}.</p>
- *
- * @param <T> Type of items in the collection.
- *
- * @since 1.1
- */
- public class DiscreteProbabilityCollectionSampler<T> implements SharedStateObjectSampler<T> {
- /** The error message for an empty collection. */
- private static final String EMPTY_COLLECTION = "Empty collection";
- /** Collection to be sampled from. */
- private final List<T> items;
- /** Sampler for the probabilities. */
- private final SharedStateDiscreteSampler sampler;
- /**
- * Creates a sampler.
- *
- * @param rng Generator of uniformly distributed random numbers.
- * @param collection Collection to be sampled, with the probabilities
- * associated to each of its items.
- * A (shallow) copy of the items will be stored in the created instance.
- * The probabilities must be non-negative, but zero values are allowed
- * and their sum does not have to equal one (input will be normalized
- * to make the probabilities sum to one).
- * @throws IllegalArgumentException if {@code collection} is empty, a
- * probability is negative, infinite or {@code NaN}, or the sum of all
- * probabilities is not strictly positive.
- */
- public DiscreteProbabilityCollectionSampler(UniformRandomProvider rng,
- Map<T, Double> collection) {
- this(toList(collection),
- createSampler(rng, toProbabilities(collection)));
- }
- /**
- * Creates a sampler.
- *
- * @param rng Generator of uniformly distributed random numbers.
- * @param collection Collection to be sampled.
- * A (shallow) copy of the items will be stored in the created instance.
- * @param probabilities Probability associated to each item of the
- * {@code collection}.
- * The probabilities must be non-negative, but zero values are allowed
- * and their sum does not have to equal one (input will be normalized
- * to make the probabilities sum to one).
- * @throws IllegalArgumentException if {@code collection} is empty or
- * a probability is negative, infinite or {@code NaN}, or if the number
- * of items in the {@code collection} is not equal to the number of
- * provided {@code probabilities}.
- */
- public DiscreteProbabilityCollectionSampler(UniformRandomProvider rng,
- List<T> collection,
- double[] probabilities) {
- this(copyList(collection),
- createSampler(rng, collection, probabilities));
- }
- /**
- * @param items Collection to be sampled.
- * @param sampler Sampler for the probabilities.
- */
- private DiscreteProbabilityCollectionSampler(List<T> items,
- SharedStateDiscreteSampler sampler) {
- this.items = items;
- this.sampler = sampler;
- }
- /**
- * Picks one of the items from the collection passed to the constructor.
- *
- * @return a random sample.
- */
- @Override
- public T sample() {
- return items.get(sampler.sample());
- }
- /**
- * {@inheritDoc}
- *
- * @since 1.3
- */
- @Override
- public DiscreteProbabilityCollectionSampler<T> withUniformRandomProvider(UniformRandomProvider rng) {
- return new DiscreteProbabilityCollectionSampler<>(items, sampler.withUniformRandomProvider(rng));
- }
- /**
- * Creates the sampler of the enumerated probability distribution.
- *
- * @param rng Generator of uniformly distributed random numbers.
- * @param probabilities Probability associated to each item.
- * @return the sampler
- */
- private static SharedStateDiscreteSampler createSampler(UniformRandomProvider rng,
- double[] probabilities) {
- return GuideTableDiscreteSampler.of(rng, probabilities);
- }
- /**
- * Creates the sampler of the enumerated probability distribution.
- *
- * @param <T> Type of items in the collection.
- * @param rng Generator of uniformly distributed random numbers.
- * @param collection Collection to be sampled.
- * @param probabilities Probability associated to each item.
- * @return the sampler
- * @throws IllegalArgumentException if the number
- * of items in the {@code collection} is not equal to the number of
- * provided {@code probabilities}.
- */
- private static <T> SharedStateDiscreteSampler createSampler(UniformRandomProvider rng,
- List<T> collection,
- double[] probabilities) {
- if (probabilities.length != collection.size()) {
- throw new IllegalArgumentException("Size mismatch: " +
- probabilities.length + " != " +
- collection.size());
- }
- return GuideTableDiscreteSampler.of(rng, probabilities);
- }
- // Validation methods exist to raise an exception before invocation of the
- // private constructor; this mitigates Finalizer attacks
- // (see SpotBugs CT_CONSTRUCTOR_THROW).
- /**
- * Extract the items.
- *
- * @param <T> Type of items in the collection.
- * @param collection Collection.
- * @return the items
- * @throws IllegalArgumentException if {@code collection} is empty.
- */
- private static <T> List<T> toList(Map<T, Double> collection) {
- if (collection.isEmpty()) {
- throw new IllegalArgumentException(EMPTY_COLLECTION);
- }
- return new ArrayList<>(collection.keySet());
- }
- /**
- * Extract the probabilities.
- *
- * @param <T> Type of items in the collection.
- * @param collection Collection.
- * @return the probabilities
- */
- private static <T> double[] toProbabilities(Map<T, Double> collection) {
- final int size = collection.size();
- final double[] probabilities = new double[size];
- int count = 0;
- for (final Double e : collection.values()) {
- final double probability = e;
- if (probability < 0 ||
- Double.isInfinite(probability) ||
- Double.isNaN(probability)) {
- throw new IllegalArgumentException("Invalid probability: " +
- probability);
- }
- probabilities[count++] = probability;
- }
- return probabilities;
- }
- /**
- * Create a (shallow) copy of the collection.
- *
- * @param <T> Type of items in the collection.
- * @param collection Collection.
- * @return the copy
- * @throws IllegalArgumentException if {@code collection} is empty.
- */
- private static <T> List<T> copyList(List<T> collection) {
- if (collection.isEmpty()) {
- throw new IllegalArgumentException(EMPTY_COLLECTION);
- }
- return new ArrayList<>(collection);
- }
- }