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‎LICENSE‎

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MIT License
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Copyright (c) 2020 Lewys Davies
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎README.md‎

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# Java-Probability-Collection
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Generic and Highly Optimised Java Data-Structure for Retrieving Random Elements With Probability

‎pom.xml‎

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<project xmlns="http://maven.apache.org/POM/4.0.0"
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<groupId>com.lewdev</groupId>
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<artifactId>probability-lib</artifactId>
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<version>0.5</version>
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<packaging>jar</packaging>
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<name>probability-lib</name>
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<url>http://example.com</url>
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<properties>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<java.version>1.8</java.version>
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<jmh.version>1.23</jmh.version>
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</properties>
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<dependencies>
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<dependency>
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<groupId>org.junit.jupiter</groupId>
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<artifactId>junit-jupiter-engine</artifactId>
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<version>5.1.0</version>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>org.hamcrest</groupId>
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<artifactId>hamcrest-core</artifactId>
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<version>1.3</version>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>org.openjdk.jmh</groupId>
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<artifactId>jmh-core</artifactId>
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<version>${jmh.version}</version>
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</dependency>
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<dependency>
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<groupId>org.openjdk.jmh</groupId>
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<artifactId>jmh-generator-annprocess</artifactId>
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<version>${jmh.version}</version>
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</dependency>
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</dependencies>
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<build>
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<plugins>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-compiler-plugin</artifactId>
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<version>3.1</version>
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<configuration>
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<source>${java.version}</source>
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<target>${java.version}</target>
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</configuration>
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</plugin>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-shade-plugin</artifactId>
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<version>3.2.0</version>
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<executions>
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<execution>
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<phase>package</phase>
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<goals>
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<goal>shade</goal>
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</goals>
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<configuration>
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<finalName>benchmarks</finalName>
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<transformers>
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<transformer
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implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
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<mainClass>org.openjdk.jmh.Main</mainClass>
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</transformer>
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</transformers>
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</configuration>
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</execution>
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</executions>
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</plugin>
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</plugins>
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</build>
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</project>

‎src/main/java/com/lewdev/probabilitylib/ProbabilityCollection.java‎

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package com.lewdev.probabilitylib;
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import java.util.Comparator;
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import java.util.Iterator;
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import java.util.TreeSet;
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import java.util.concurrent.ThreadLocalRandom;
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/**
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* ProbabilityCollection for retrieving random elements based on probability.
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* <br>
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* <br>
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* <b>Selection Algorithm Implementation</b>:
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* <p>
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* <ul>
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* <li>Elements have a "block" of space, sized based on their probability share
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* <li>"Blocks" start from index 1 and end at the total probability of all elements
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* <li>A random number is selected between 1 and the total probability
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* <li>Which "block" the random number falls in is the element that is selected
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* <li>Therefore "block"s with larger probability have a greater chance of being
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* selected than those with smaller probability.
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* </p>
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* </ul>
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*
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* @author Lewys Davies
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*
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* @param <E> Type of elements
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*/
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public class ProbabilityCollection<E> {
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protected final Comparator<ProbabilitySetElement<E>> comparator =
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(o1, o2)-> Integer.compare(o1.getIndex(), o2.getIndex());
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private final TreeSet<ProbabilitySetElement<E>> collection;
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private int totalProbability;
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/**
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* Construct a new Probability Collection
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*/
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public ProbabilityCollection() {
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this.collection = new TreeSet<>(this.comparator);
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this.totalProbability = 0;
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}
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/**
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* @return Number of objects inside the collection
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*/
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public int size() {
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return this.collection.size();
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}
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/**
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* @return Collection contains no elements
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*/
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public boolean isEmpty() {
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return this.collection.isEmpty();
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}
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/**
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* @param object
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* @return True if the collection contains the object, else False
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*/
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public boolean contains(E object) {
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return this.collection.stream()
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.filter(entry -> entry.getObject().equals(object))
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.findFirst()
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.isPresent();
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}
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/**
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* @return Iterator over collection
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*/
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public Iterator<ProbabilitySetElement<E>> iterator() {
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return this.collection.iterator();
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}
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/**
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* Add an object to this collection
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*
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* @param object
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* @param probability share
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*/
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public void add(E object, int probability) {
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this.collection.add(new ProbabilitySetElement<E>(object, probability));
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this.totalProbability += probability;
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this.updateIndexes();
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}
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/**
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* Remove a object from this collection
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*
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* @param object
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* @return True if object was removed, else False.
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*/
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public boolean remove(E object) {
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Iterator<ProbabilitySetElement<E>> it = this.iterator();
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boolean removed = false;
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while(it.hasNext()) {
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ProbabilitySetElement<E> element = it.next();
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if(element.getObject().equals(object)) {
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removed = true;
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this.totalProbability -= element.getProbability();
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it.remove();
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}
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}
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this.updateIndexes();
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return removed;
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}
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/**
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* @return Random object based on probability
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*/
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public E get() {
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ProbabilitySetElement<E> toFind = new ProbabilitySetElement<>(null, 0);
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toFind.setIndex(ThreadLocalRandom.current().nextInt(1, this.totalProbability + 1));
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return this.collection.floor(toFind).getObject();
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}
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/**
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* @return Sum of all element's probability
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*/
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public final int getTotalProbability() {
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return this.totalProbability;
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}
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/*
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* Calculate the size of all element's "block" of space:
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* i.e 1-5, 6-10, 11-14, 15, 16
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*
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* We then only need to store the start index of each element
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*/
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private void updateIndexes() {
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int previousIndex = 0;
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for(ProbabilitySetElement<E> entry : this.collection) {
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previousIndex = entry.setIndex(previousIndex + 1) + (entry.getProbability() - 1);
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}
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}
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/**
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* Used internally to store information about a object's
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* state in a collection. Specifically, the probability
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* and index within the collection.
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*
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* Indexes refer to the start position of this element's "block" of space.
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* The space between element "block"s represents their probability of being selected
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*
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* @author Lewys Davies
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*
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* @param <T> Type of element
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*/
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final static class ProbabilitySetElement<T> {
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private final T object;
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private final int probability;
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private int index;
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/**
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* @param object
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* @param probability
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*/
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protected ProbabilitySetElement(T object, int probability) {
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this.object = object;
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this.probability = probability;
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}
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/**
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* @return The actual object
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*/
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public final T getObject() {
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return this.object;
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}
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/**
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* @return Probability share in this collection
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*/
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public final int getProbability() {
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return this.probability;
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}
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// Used internally, see this class's documentation
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protected final int getIndex() {
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return this.index;
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}
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// Used Internally, see this class's documentation
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protected final int setIndex(int index) {
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this.index = index;
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return this.index;
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}
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}
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}

‎src/test/java/com/lewdev/probabilitylib/BenchmarkProbability.java‎

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package com.lewdev.probabilitylib;
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import java.util.HashMap;
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import java.util.Map;
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import java.util.concurrent.TimeUnit;
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import org.openjdk.jmh.annotations.Benchmark;
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import org.openjdk.jmh.annotations.BenchmarkMode;
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import org.openjdk.jmh.annotations.Measurement;
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import org.openjdk.jmh.annotations.Mode;
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import org.openjdk.jmh.annotations.Scope;
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import org.openjdk.jmh.annotations.Setup;
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import org.openjdk.jmh.annotations.State;
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import org.openjdk.jmh.annotations.Timeout;
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import org.openjdk.jmh.annotations.Warmup;
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import org.openjdk.jmh.infra.Blackhole;
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import org.openjdk.jmh.runner.Runner;
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import org.openjdk.jmh.runner.RunnerException;
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import org.openjdk.jmh.runner.options.Options;
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import org.openjdk.jmh.runner.options.OptionsBuilder;
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@BenchmarkMode(Mode.AverageTime)
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@State(Scope.Benchmark)
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@Warmup(iterations = 5, time = 5)
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@Timeout(time = 25, timeUnit = TimeUnit.SECONDS)
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@Measurement(iterations = 10, time = 2)
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public class BenchmarkProbability {
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public static void main(String[] args) throws RunnerException {
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Options opt = new OptionsBuilder()
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.include(BenchmarkProbability.class.getSimpleName())
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.forks(1)
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.build();
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new Runner(opt).run();
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}
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private final int elements = 10_000;
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ProbabilityMap<Integer> map = new ProbabilityMap<>();
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ProbabilityCollection<Integer> collection = new ProbabilityCollection<>();
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private Map<Integer, Integer> addAllTest = new HashMap<>();
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@Setup
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public void setup() {
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for(int i = 0; i < elements; i++) {
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map.add(i, 1);
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collection.add(i, 1);
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}
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for(int i = elements; i < elements * 2; i++) {
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addAllTest.put(i, 1);
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}
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}
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@Benchmark
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public void mapAddSingle(Blackhole bh) {
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boolean added = this.map.add(25000, 1);
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bh.consume(added);
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}
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@Benchmark
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public void mapAddAll() {
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map.addAll(addAllTest);
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}
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@Benchmark
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public void collectionAddSingle() {
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this.collection.add(25000, 1);
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}
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@Benchmark
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public void mapGet(Blackhole bh) {
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for(int i = 0; i < elements * 2; i++) {
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bh.consume(map.get());
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}
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}
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@Benchmark
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public void collectionGet(Blackhole bh) {
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for(int i = 0; i < elements * 2; i++) {
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bh.consume(collection.get());
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}
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}
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}

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