Merge remote-tracking branch 'upstream/master'

This commit is contained in:
Justin Albano
2019-09-13 21:14:15 -04:00
1592 changed files with 248419 additions and 8393 deletions
-24
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@@ -1,24 +0,0 @@
language: java
before_install:
- echo "MAVEN_OPTS='-Xmx2048M -Xss128M -XX:+CMSClassUnloadingEnabled -XX:+UseG1GC -XX:-UseGCOverheadLimit'" > ~/.mavenrc
install: skip
script: travis_wait 60 mvn -q install -Pdefault-first,default-second -Dgib.enabled=true
sudo: required
jdk:
- oraclejdk8
addons:
apt:
packages:
- oracle-java8-installer
cache:
directories:
- .autoconf
- $HOME/.m2
+1
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@@ -7,3 +7,4 @@
- [Checking If a List Is Sorted in Java](https://www.baeldung.com/java-check-if-list-sorted)
- [Checking if a Java Graph has a Cycle](https://www.baeldung.com/java-graph-has-a-cycle)
- [A Guide to the Folding Technique in Java](https://www.baeldung.com/folding-hashing-technique)
- [Creating a Triangle with for Loops in Java](https://www.baeldung.com/java-print-triangle)
+34 -9
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@@ -1,5 +1,5 @@
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<artifactId>algorithms-miscellaneous-3</artifactId>
<version>0.0.1-SNAPSHOT</version>
@@ -18,17 +18,41 @@
<version>${org.assertj.core.version}</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-collections4</artifactId>
<version>${commons-collections4.version}</version>
<groupId>org.apache.commons</groupId>
<artifactId>commons-collections4</artifactId>
<version>${commons-collections4.version}</version>
</dependency>
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>${guava.version}</version>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>${guava.version}</version>
</dependency>
<dependency>
<groupId>com.squareup.retrofit2</groupId>
<artifactId>retrofit</artifactId>
<version>${retrofit.version}</version>
</dependency>
<dependency>
<groupId>com.squareup.retrofit2</groupId>
<artifactId>converter-jackson</artifactId>
<version>${retrofit.version}</version>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
<version>3.8.1</version>
</dependency>
<dependency>
<groupId>pl.pragmatists</groupId>
<artifactId>JUnitParams</artifactId>
<version>1.1.0</version>
<scope>test</scope>
</dependency>
</dependencies>
@@ -48,5 +72,6 @@
<org.assertj.core.version>3.9.0</org.assertj.core.version>
<commons-collections4.version>4.3</commons-collections4.version>
<guava.version>28.0-jre</guava.version>
<retrofit.version>2.6.0</retrofit.version>
</properties>
</project>
@@ -0,0 +1,70 @@
package com.baeldung.bucketsort;
import java.util.ArrayList;
import java.util.Comparator;
import java.util.List;
public class IntegerBucketSorter implements Sorter<Integer> {
private final Comparator<Integer> comparator;
public IntegerBucketSorter(Comparator<Integer> comparator) {
this.comparator = comparator;
}
public IntegerBucketSorter() {
comparator = Comparator.naturalOrder();
}
public List<Integer> sort(List<Integer> arrayToSort) {
List<List<Integer>> buckets = splitIntoUnsortedBuckets(arrayToSort);
for(List<Integer> bucket : buckets){
bucket.sort(comparator);
}
return concatenateSortedBuckets(buckets);
}
private List<Integer> concatenateSortedBuckets(List<List<Integer>> buckets){
List<Integer> sortedArray = new ArrayList<>();
int index = 0;
for(List<Integer> bucket : buckets){
for(int number : bucket){
sortedArray.add(index++, number);
}
}
return sortedArray;
}
private List<List<Integer>> splitIntoUnsortedBuckets(List<Integer> initialList){
final int[] codes = createHashes(initialList);
List<List<Integer>> buckets = new ArrayList<>(codes[1]);
for(int i = 0; i < codes[1]; i++) buckets.add(new ArrayList<>());
//distribute the data
for (int i : initialList) {
buckets.get(hash(i, codes)).add(i);
}
return buckets;
}
private int[] createHashes(List<Integer> input){
int m = input.get(0);
for (int i = 1; i < input.size(); i++) {
if (m < input.get(i)) {
m = input.get(i);
}
}
return new int[]{m, (int) Math.sqrt(input.size())};
}
private static int hash(int i, int[] code) {
return (int) ((double) i / code[0] * (code[1] - 1));
}
}
@@ -0,0 +1,8 @@
package com.baeldung.bucketsort;
import java.util.List;
public interface Sorter<T> {
List<T> sort(List<T> arrayToSort);
}
@@ -0,0 +1,35 @@
package com.baeldung.algorithms.interpolationsearch;
public class InterpolationSearch {
public static int interpolationSearch(int[] data, int item) {
int highEnd = (data.length - 1);
int lowEnd = 0;
while (item >= data[lowEnd] && item <= data[highEnd] && lowEnd <= highEnd) {
int probe = lowEnd + (highEnd - lowEnd) * (item - data[lowEnd]) / (data[highEnd] - data[lowEnd]);
if (highEnd == lowEnd) {
if (data[lowEnd] == item) {
return lowEnd;
} else {
return -1;
}
}
if (data[probe] == item) {
return probe;
}
if (data[probe] < item) {
lowEnd = probe + 1;
} else {
highEnd = probe - 1;
}
}
return -1;
}
}
@@ -0,0 +1,45 @@
package com.baeldung.algorithms.kmeans;
import java.util.Map;
import java.util.Objects;
/**
* Encapsulates all coordinates for a particular cluster centroid.
*/
public class Centroid {
/**
* The centroid coordinates.
*/
private final Map<String, Double> coordinates;
public Centroid(Map<String, Double> coordinates) {
this.coordinates = coordinates;
}
public Map<String, Double> getCoordinates() {
return coordinates;
}
@Override
public boolean equals(Object o) {
if (this == o) {
return true;
}
if (o == null || getClass() != o.getClass()) {
return false;
}
Centroid centroid = (Centroid) o;
return Objects.equals(getCoordinates(), centroid.getCoordinates());
}
@Override
public int hashCode() {
return Objects.hash(getCoordinates());
}
@Override
public String toString() {
return "Centroid " + coordinates;
}
}
@@ -0,0 +1,20 @@
package com.baeldung.algorithms.kmeans;
import java.util.Map;
/**
* Defines a contract to calculate distance between two feature vectors. The less the
* calculated distance, the more two items are similar to each other.
*/
public interface Distance {
/**
* Calculates the distance between two feature vectors.
*
* @param f1 The first set of features.
* @param f2 The second set of features.
* @return Calculated distance.
* @throws IllegalArgumentException If the given feature vectors are invalid.
*/
double calculate(Map<String, Double> f1, Map<String, Double> f2);
}
@@ -0,0 +1,23 @@
package com.baeldung.algorithms.kmeans;
import java.util.List;
import java.util.Map;
/**
* Encapsulates methods to calculates errors between centroid and the cluster members.
*/
public class Errors {
public static double sse(Map<Centroid, List<Record>> clustered, Distance distance) {
double sum = 0;
for (Map.Entry<Centroid, List<Record>> entry : clustered.entrySet()) {
Centroid centroid = entry.getKey();
for (Record record : entry.getValue()) {
double d = distance.calculate(centroid.getCoordinates(), record.getFeatures());
sum += Math.pow(d, 2);
}
}
return sum;
}
}
@@ -0,0 +1,26 @@
package com.baeldung.algorithms.kmeans;
import java.util.Map;
/**
* Calculates the distance between two items using the Euclidean formula.
*/
public class EuclideanDistance implements Distance {
@Override
public double calculate(Map<String, Double> f1, Map<String, Double> f2) {
if (f1 == null || f2 == null) {
throw new IllegalArgumentException("Feature vectors can't be null");
}
double sum = 0;
for (String key : f1.keySet()) {
Double v1 = f1.get(key);
Double v2 = f2.get(key);
if (v1 != null && v2 != null) sum += Math.pow(v1 - v2, 2);
}
return Math.sqrt(sum);
}
}
@@ -0,0 +1,236 @@
package com.baeldung.algorithms.kmeans;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Random;
import java.util.Set;
import static java.util.stream.Collectors.toList;
import static java.util.stream.Collectors.toSet;
/**
* Encapsulates an implementation of KMeans clustering algorithm.
*
* @author Ali Dehghani
*/
public class KMeans {
private KMeans() {
throw new IllegalAccessError("You shouldn't call this constructor");
}
/**
* Will be used to generate random numbers.
*/
private static final Random random = new Random();
/**
* Performs the K-Means clustering algorithm on the given dataset.
*
* @param records The dataset.
* @param k Number of Clusters.
* @param distance To calculate the distance between two items.
* @param maxIterations Upper bound for the number of iterations.
* @return K clusters along with their features.
*/
public static Map<Centroid, List<Record>> fit(List<Record> records, int k, Distance distance, int maxIterations) {
applyPreconditions(records, k, distance, maxIterations);
List<Centroid> centroids = randomCentroids(records, k);
Map<Centroid, List<Record>> clusters = new HashMap<>();
Map<Centroid, List<Record>> lastState = new HashMap<>();
// iterate for a pre-defined number of times
for (int i = 0; i < maxIterations; i++) {
boolean isLastIteration = i == maxIterations - 1;
// in each iteration we should find the nearest centroid for each record
for (Record record : records) {
Centroid centroid = nearestCentroid(record, centroids, distance);
assignToCluster(clusters, record, centroid);
}
// if the assignment does not change, then the algorithm terminates
boolean shouldTerminate = isLastIteration || clusters.equals(lastState);
lastState = clusters;
if (shouldTerminate) {
break;
}
// at the end of each iteration we should relocate the centroids
centroids = relocateCentroids(clusters);
clusters = new HashMap<>();
}
return lastState;
}
/**
* Move all cluster centroids to the average of all assigned features.
*
* @param clusters The current cluster configuration.
* @return Collection of new and relocated centroids.
*/
private static List<Centroid> relocateCentroids(Map<Centroid, List<Record>> clusters) {
return clusters
.entrySet()
.stream()
.map(e -> average(e.getKey(), e.getValue()))
.collect(toList());
}
/**
* Moves the given centroid to the average position of all assigned features. If
* the centroid has no feature in its cluster, then there would be no need for a
* relocation. Otherwise, for each entry we calculate the average of all records
* first by summing all the entries and then dividing the final summation value by
* the number of records.
*
* @param centroid The centroid to move.
* @param records The assigned features.
* @return The moved centroid.
*/
private static Centroid average(Centroid centroid, List<Record> records) {
// if this cluster is empty, then we shouldn't move the centroid
if (records == null || records.isEmpty()) {
return centroid;
}
// Since some records don't have all possible attributes, we initialize
// average coordinates equal to current centroid coordinates
Map<String, Double> average = centroid.getCoordinates();
// The average function works correctly if we clear all coordinates corresponding
// to present record attributes
records
.stream()
.flatMap(e -> e
.getFeatures()
.keySet()
.stream())
.forEach(k -> average.put(k, 0.0));
for (Record record : records) {
record
.getFeatures()
.forEach((k, v) -> average.compute(k, (k1, currentValue) -> v + currentValue));
}
average.forEach((k, v) -> average.put(k, v / records.size()));
return new Centroid(average);
}
/**
* Assigns a feature vector to the given centroid. If this is the first assignment for this centroid,
* first we should create the list.
*
* @param clusters The current cluster configuration.
* @param record The feature vector.
* @param centroid The centroid.
*/
private static void assignToCluster(Map<Centroid, List<Record>> clusters, Record record, Centroid centroid) {
clusters.compute(centroid, (key, list) -> {
if (list == null) {
list = new ArrayList<>();
}
list.add(record);
return list;
});
}
/**
* With the help of the given distance calculator, iterates through centroids and finds the
* nearest one to the given record.
*
* @param record The feature vector to find a centroid for.
* @param centroids Collection of all centroids.
* @param distance To calculate the distance between two items.
* @return The nearest centroid to the given feature vector.
*/
private static Centroid nearestCentroid(Record record, List<Centroid> centroids, Distance distance) {
double minimumDistance = Double.MAX_VALUE;
Centroid nearest = null;
for (Centroid centroid : centroids) {
double currentDistance = distance.calculate(record.getFeatures(), centroid.getCoordinates());
if (currentDistance < minimumDistance) {
minimumDistance = currentDistance;
nearest = centroid;
}
}
return nearest;
}
/**
* Generates k random centroids. Before kicking-off the centroid generation process,
* first we calculate the possible value range for each attribute. Then when
* we're going to generate the centroids, we generate random coordinates in
* the [min, max] range for each attribute.
*
* @param records The dataset which helps to calculate the [min, max] range for
* each attribute.
* @param k Number of clusters.
* @return Collections of randomly generated centroids.
*/
private static List<Centroid> randomCentroids(List<Record> records, int k) {
List<Centroid> centroids = new ArrayList<>();
Map<String, Double> maxs = new HashMap<>();
Map<String, Double> mins = new HashMap<>();
for (Record record : records) {
record
.getFeatures()
.forEach((key, value) -> {
// compares the value with the current max and choose the bigger value between them
maxs.compute(key, (k1, max) -> max == null || value > max ? value : max);
// compare the value with the current min and choose the smaller value between them
mins.compute(key, (k1, min) -> min == null || value < min ? value : min);
});
}
Set<String> attributes = records
.stream()
.flatMap(e -> e
.getFeatures()
.keySet()
.stream())
.collect(toSet());
for (int i = 0; i < k; i++) {
Map<String, Double> coordinates = new HashMap<>();
for (String attribute : attributes) {
double max = maxs.get(attribute);
double min = mins.get(attribute);
coordinates.put(attribute, random.nextDouble() * (max - min) + min);
}
centroids.add(new Centroid(coordinates));
}
return centroids;
}
private static void applyPreconditions(List<Record> records, int k, Distance distance, int maxIterations) {
if (records == null || records.isEmpty()) {
throw new IllegalArgumentException("The dataset can't be empty");
}
if (k <= 1) {
throw new IllegalArgumentException("It doesn't make sense to have less than or equal to 1 cluster");
}
if (distance == null) {
throw new IllegalArgumentException("The distance calculator is required");
}
if (maxIterations <= 0) {
throw new IllegalArgumentException("Max iterations should be a positive number");
}
}
}
@@ -0,0 +1,144 @@
package com.baeldung.algorithms.kmeans;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.stream.Collectors;
import com.fasterxml.jackson.databind.ObjectMapper;
import okhttp3.OkHttpClient;
import retrofit2.Retrofit;
import retrofit2.converter.jackson.JacksonConverterFactory;
import static java.util.stream.Collectors.toSet;
public class LastFm {
private static OkHttpClient okHttp = new OkHttpClient.Builder()
.addInterceptor(new LastFmService.Authenticator("put your API key here"))
.build();
private static Retrofit retrofit = new Retrofit.Builder()
.client(okHttp)
.addConverterFactory(JacksonConverterFactory.create())
.baseUrl("http://ws.audioscrobbler.com/")
.build();
private static LastFmService lastFm = retrofit.create(LastFmService.class);
private static ObjectMapper mapper = new ObjectMapper();
public static void main(String[] args) throws IOException {
List<String> artists = getTop100Artists();
Set<String> tags = getTop100Tags();
List<Record> records = datasetWithTaggedArtists(artists, tags);
Map<Centroid, List<Record>> clusters = KMeans.fit(records, 7, new EuclideanDistance(), 1000);
// Print the cluster configuration
clusters.forEach((key, value) -> {
System.out.println("------------------------------ CLUSTER -----------------------------------");
System.out.println(sortedCentroid(key));
String members = String.join(", ", value
.stream()
.map(Record::getDescription)
.collect(toSet()));
System.out.print(members);
System.out.println();
System.out.println();
});
Map<String, Object> json = convertToD3CompatibleMap(clusters);
System.out.println(mapper.writeValueAsString(json));
}
private static Map<String, Object> convertToD3CompatibleMap(Map<Centroid, List<Record>> clusters) {
Map<String, Object> json = new HashMap<>();
json.put("name", "Musicians");
List<Map<String, Object>> children = new ArrayList<>();
clusters.forEach((key, value) -> {
Map<String, Object> child = new HashMap<>();
child.put("name", dominantGenre(sortedCentroid(key)));
List<Map<String, String>> nested = new ArrayList<>();
for (Record record : value) {
nested.add(Collections.singletonMap("name", record.getDescription()));
}
child.put("children", nested);
children.add(child);
});
json.put("children", children);
return json;
}
private static String dominantGenre(Centroid centroid) {
return centroid
.getCoordinates()
.keySet()
.stream()
.limit(2)
.collect(Collectors.joining(", "));
}
private static Centroid sortedCentroid(Centroid key) {
List<Map.Entry<String, Double>> entries = new ArrayList<>(key
.getCoordinates()
.entrySet());
entries.sort((e1, e2) -> e2
.getValue()
.compareTo(e1.getValue()));
Map<String, Double> sorted = new LinkedHashMap<>();
for (Map.Entry<String, Double> entry : entries) {
sorted.put(entry.getKey(), entry.getValue());
}
return new Centroid(sorted);
}
private static List<Record> datasetWithTaggedArtists(List<String> artists, Set<String> topTags) throws IOException {
List<Record> records = new ArrayList<>();
for (String artist : artists) {
Map<String, Double> tags = lastFm
.topTagsFor(artist)
.execute()
.body()
.all();
// Only keep popular tags.
tags
.entrySet()
.removeIf(e -> !topTags.contains(e.getKey()));
records.add(new Record(artist, tags));
}
return records;
}
private static Set<String> getTop100Tags() throws IOException {
return lastFm
.topTags()
.execute()
.body()
.all();
}
private static List<String> getTop100Artists() throws IOException {
List<String> artists = new ArrayList<>();
for (int i = 1; i <= 2; i++) {
artists.addAll(lastFm
.topArtists(i)
.execute()
.body()
.all());
}
return artists;
}
}
@@ -0,0 +1,118 @@
package com.baeldung.algorithms.kmeans;
import java.io.IOException;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.stream.Collectors;
import com.fasterxml.jackson.annotation.JsonAutoDetect;
import com.fasterxml.jackson.annotation.JsonProperty;
import okhttp3.HttpUrl;
import okhttp3.Interceptor;
import okhttp3.Request;
import okhttp3.Response;
import retrofit2.Call;
import retrofit2.http.GET;
import retrofit2.http.Query;
import static com.fasterxml.jackson.annotation.JsonAutoDetect.Visibility.ANY;
import static java.util.stream.Collectors.toList;
public interface LastFmService {
@GET("/2.0/?method=chart.gettopartists&format=json&limit=50")
Call<Artists> topArtists(@Query("page") int page);
@GET("/2.0/?method=artist.gettoptags&format=json&limit=20&autocorrect=1")
Call<Tags> topTagsFor(@Query("artist") String artist);
@GET("/2.0/?method=chart.gettoptags&format=json&limit=100")
Call<TopTags> topTags();
/**
* HTTP interceptor to intercept all HTTP requests and add the API key to them.
*/
class Authenticator implements Interceptor {
private final String apiKey;
Authenticator(String apiKey) {
this.apiKey = apiKey;
}
@Override
public Response intercept(Chain chain) throws IOException {
HttpUrl url = chain
.request()
.url()
.newBuilder()
.addQueryParameter("api_key", apiKey)
.build();
Request request = chain
.request()
.newBuilder()
.url(url)
.build();
return chain.proceed(request);
}
}
@JsonAutoDetect(fieldVisibility = ANY)
class TopTags {
private Map<String, Object> tags;
@SuppressWarnings("unchecked")
public Set<String> all() {
List<Map<String, Object>> topTags = (List<Map<String, Object>>) tags.get("tag");
return topTags
.stream()
.map(e -> ((String) e.get("name")))
.collect(Collectors.toSet());
}
}
@JsonAutoDetect(fieldVisibility = ANY)
class Tags {
@JsonProperty("toptags") private Map<String, Object> topTags;
@SuppressWarnings("unchecked")
public Map<String, Double> all() {
try {
Map<String, Double> all = new HashMap<>();
List<Map<String, Object>> tags = (List<Map<String, Object>>) topTags.get("tag");
for (Map<String, Object> tag : tags) {
all.put(((String) tag.get("name")), ((Integer) tag.get("count")).doubleValue());
}
return all;
} catch (Exception e) {
return Collections.emptyMap();
}
}
}
@JsonAutoDetect(fieldVisibility = ANY)
class Artists {
private Map<String, Object> artists;
@SuppressWarnings("unchecked")
public List<String> all() {
try {
List<Map<String, Object>> artists = (List<Map<String, Object>>) this.artists.get("artist");
return artists
.stream()
.map(e -> ((String) e.get("name")))
.collect(toList());
} catch (Exception e) {
return Collections.emptyList();
}
}
}
}
@@ -0,0 +1,65 @@
package com.baeldung.algorithms.kmeans;
import java.util.Map;
import java.util.Objects;
/**
* Encapsulates all feature values for a few attributes. Optionally each record
* can be described with the {@link #description} field.
*/
public class Record {
/**
* The record description. For example, this can be the artist name for the famous musician
* example.
*/
private final String description;
/**
* Encapsulates all attributes and their corresponding values, i.e. features.
*/
private final Map<String, Double> features;
public Record(String description, Map<String, Double> features) {
this.description = description;
this.features = features;
}
public Record(Map<String, Double> features) {
this("", features);
}
public String getDescription() {
return description;
}
public Map<String, Double> getFeatures() {
return features;
}
@Override
public String toString() {
String prefix = description == null || description
.trim()
.isEmpty() ? "Record" : description;
return prefix + ": " + features;
}
@Override
public boolean equals(Object o) {
if (this == o) {
return true;
}
if (o == null || getClass() != o.getClass()) {
return false;
}
Record record = (Record) o;
return Objects.equals(getDescription(), record.getDescription()) && Objects.equals(getFeatures(), record.getFeatures());
}
@Override
public int hashCode() {
return Objects.hash(getDescription(), getFeatures());
}
}
@@ -0,0 +1,61 @@
package com.baeldung.algorithms.printtriangles;
import org.apache.commons.lang3.StringUtils;
public class PrintTriangleExamples {
public static String printARightTriangle(int N) {
StringBuilder result = new StringBuilder();
for (int r = 1; r <= N; r++) {
for (int j = 1; j <= r; j++) {
result.append("*");
}
result.append(System.lineSeparator());
}
return result.toString();
}
public static String printAnIsoscelesTriangle(int N) {
StringBuilder result = new StringBuilder();
for (int r = 1; r <= N; r++) {
for (int sp = 1; sp <= N - r; sp++) {
result.append(" ");
}
for (int c = 1; c <= (r * 2) - 1; c++) {
result.append("*");
}
result.append(System.lineSeparator());
}
return result.toString();
}
public static String printAnIsoscelesTriangleUsingStringUtils(int N) {
StringBuilder result = new StringBuilder();
for (int r = 1; r <= N; r++) {
result.append(StringUtils.repeat(' ', N - r));
result.append(StringUtils.repeat('*', 2 * r - 1));
result.append(System.lineSeparator());
}
return result.toString();
}
public static String printAnIsoscelesTriangleUsingSubstring(int N) {
StringBuilder result = new StringBuilder();
String helperString = StringUtils.repeat(' ', N - 1) + StringUtils.repeat('*', N * 2 - 1);
for (int r = 0; r < N; r++) {
result.append(helperString.substring(r, N + 2 * r));
result.append(System.lineSeparator());
}
return result.toString();
}
public static void main(String[] args) {
System.out.println(printARightTriangle(5));
System.out.println(printAnIsoscelesTriangle(5));
System.out.println(printAnIsoscelesTriangleUsingStringUtils(5));
System.out.println(printAnIsoscelesTriangleUsingSubstring(5));
}
}
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@@ -0,0 +1,68 @@
<!DOCTYPE html>
<meta charset="utf-8">
<style>
.node circle {
fill: #fff;
stroke: steelblue;
stroke-width: 1.5px;
}
.node {
font: 10px sans-serif;
}
.link {
fill: none;
stroke: #ccc;
stroke-width: 1.5px;
}
</style>
<body>
<script src="http://d3js.org/d3.v3.min.js"></script>
<script>
var diameter = 1100;
var tree = d3.layout.tree()
.size([360, diameter / 2 - 300])
.separation(function (a, b) {
return (a.parent == b.parent ? 1 : 2) / a.depth;
});
var diagonal = d3.svg.diagonal.radial()
.projection(function (d) {
return [d.y, d.x / 180 * Math.PI];
});
var svg = d3.select("body").append("svg")
.attr("width", diameter)
.attr("height", diameter - 150)
.append("g")
.attr("transform", "translate(" + diameter / 2 + "," + diameter / 2 + ")");
d3.json("lastfm.json", function (error, root) {
var nodes = tree.nodes(root),
links = tree.links(nodes);
var link = svg.selectAll(".link")
.data(links)
.enter().append("path")
.attr("class", "link")
.attr("d", diagonal);
var node = svg.selectAll(".node")
.data(nodes)
.enter().append("g")
.attr("class", "node")
.attr("transform", function (d) {
return "rotate(" + (d.x - 90) + ")translate(" + d.y + ")";
})
node.append("circle")
.attr("r", 4.5);
node.append("text")
.attr("dy", ".31em")
.attr("text-anchor", function (d) {
return d.x < 180 ? "start" : "end";
})
.attr("transform", function (d) {
return d.x < 180 ? "translate(8)" : "rotate(180)translate(-8)";
})
.text(function (d) {
return d.name;
});
});
d3.select(self.frameElement).style("height", diameter - 150 + "px");
</script>
@@ -0,0 +1,33 @@
package com.baeldung.bucketsort;
import com.baeldung.bucketsort.IntegerBucketSorter;
import org.junit.Before;
import org.junit.Test;
import java.util.Arrays;
import java.util.List;
import static org.junit.Assert.assertEquals;
public class IntegerBucketSorterUnitTest {
private IntegerBucketSorter sorter;
@Before
public void setUp() throws Exception {
sorter = new IntegerBucketSorter();
}
@Test
public void givenUnsortedList_whenSortedUsingBucketSorter_checkSortingCorrect() {
List<Integer> unsorted = Arrays.asList(80,50,60,30,20,10,70,0,40,500,600,602,200,15);
List<Integer> expected = Arrays.asList(0,10,15,20,30,40,50,60,70,80,200,500,600,602);
List<Integer> actual = sorter.sort(unsorted);
assertEquals(expected, actual);
}
}
@@ -0,0 +1,29 @@
package com.baeldung.algorithms.interpolationsearch;
import static org.junit.jupiter.api.Assertions.assertEquals;
import org.junit.Before;
import org.junit.Test;
public class InterpolationSearchUnitTest {
private int[] myData;
@Before
public void setUp() {
myData = new int[]{13,21,34,55,69,73,84,101};
}
@Test
public void givenSortedArray_whenLookingFor84_thenReturn6() {
int pos = InterpolationSearch.interpolationSearch(myData, 84);
assertEquals(6, pos);
}
@Test
public void givenSortedArray_whenLookingFor19_thenReturnMinusOne() {
int pos = InterpolationSearch.interpolationSearch(myData, 19);
assertEquals(-1, pos);
}
}
@@ -0,0 +1,101 @@
package com.baeldung.algorithms.printtriangles;
import junitparams.JUnitParamsRunner;
import junitparams.Parameters;
import org.junit.Test;
import org.junit.runner.RunWith;
import static org.junit.Assert.assertEquals;
@RunWith(JUnitParamsRunner.class)
public class PrintTriangleExamplesUnitTest {
private static Object[][] rightTriangles() {
String expected0 = "";
String expected2 = "*" + System.lineSeparator()
+ "**" + System.lineSeparator();
String expected5 = "*" + System.lineSeparator()
+ "**" + System.lineSeparator()
+ "***" + System.lineSeparator()
+ "****" + System.lineSeparator()
+ "*****" + System.lineSeparator();
String expected7 = "*" + System.lineSeparator()
+ "**" + System.lineSeparator()
+ "***" + System.lineSeparator()
+ "****" + System.lineSeparator()
+ "*****" + System.lineSeparator()
+ "******" + System.lineSeparator()
+ "*******" + System.lineSeparator();
return new Object[][] {
{ 0, expected0 },
{ 2, expected2 },
{ 5, expected5 },
{ 7, expected7 }
};
}
@Test
@Parameters(method = "rightTriangles")
public void whenPrintARightTriangleIsCalled_ThenTheCorrectStringIsReturned(int nrOfRows, String expected) {
String actual = PrintTriangleExamples.printARightTriangle(nrOfRows);
assertEquals(expected, actual);
}
private static Object[][] isoscelesTriangles() {
String expected0 = "";
String expected2 = " *" + System.lineSeparator()
+ "***" + System.lineSeparator();
String expected5 = " *" + System.lineSeparator()
+ " ***" + System.lineSeparator()
+ " *****" + System.lineSeparator()
+ " *******" + System.lineSeparator()
+ "*********" + System.lineSeparator();
String expected7 = " *" + System.lineSeparator()
+ " ***" + System.lineSeparator()
+ " *****" + System.lineSeparator()
+ " *******" + System.lineSeparator()
+ " *********" + System.lineSeparator()
+ " ***********" + System.lineSeparator()
+ "*************" + System.lineSeparator();
return new Object[][] {
{ 0, expected0 },
{ 2, expected2 },
{ 5, expected5 },
{ 7, expected7 }
};
}
@Test
@Parameters(method = "isoscelesTriangles")
public void whenPrintAnIsoscelesTriangleIsCalled_ThenTheCorrectStringIsReturned(int nrOfRows, String expected) {
String actual = PrintTriangleExamples.printAnIsoscelesTriangle(nrOfRows);
assertEquals(expected, actual);
}
@Test
@Parameters(method = "isoscelesTriangles")
public void whenPrintAnIsoscelesTriangleUsingStringUtilsIsCalled_ThenTheCorrectStringIsReturned(int nrOfRows, String expected) {
String actual = PrintTriangleExamples.printAnIsoscelesTriangleUsingStringUtils(nrOfRows);
assertEquals(expected, actual);
}
@Test
@Parameters(method = "isoscelesTriangles")
public void whenPrintAnIsoscelesTriangleUsingSubstringIsCalled_ThenTheCorrectStringIsReturned(int nrOfRows, String expected) {
String actual = PrintTriangleExamples.printAnIsoscelesTriangleUsingSubstring(nrOfRows);
assertEquals(expected, actual);
}
}
+2
View File
@@ -5,3 +5,5 @@
- [Quicksort Algorithm Implementation in Java](https://www.baeldung.com/java-quicksort)
- [Insertion Sort in Java](https://www.baeldung.com/java-insertion-sort)
- [Heap Sort in Java](https://www.baeldung.com/java-heap-sort)
- [Shell Sort in Java](https://www.baeldung.com/java-shell-sort)
- [Counting Sort in Java](https://www.baeldung.com/java-counting-sort)
@@ -0,0 +1,48 @@
package com.baeldung.algorithms.counting;
import java.util.Arrays;
import java.util.stream.IntStream;
public class CountingSort {
public static int[] sort(int[] input, int k) {
verifyPreconditions(input, k);
if (input.length == 0) return input;
int[] c = countElements(input, k);
int[] sorted = new int[input.length];
for (int i = input.length - 1; i >= 0; i--) {
int current = input[i];
sorted[c[current] - 1] = current;
c[current] -= 1;
}
return sorted;
}
static int[] countElements(int[] input, int k) {
int[] c = new int[k + 1];
Arrays.fill(c, 0);
for (int i : input) {
c[i] += 1;
}
for (int i = 1; i < c.length; i++) {
c[i] += c[i - 1];
}
return c;
}
private static void verifyPreconditions(int[] input, int k) {
if (input == null) {
throw new IllegalArgumentException("Input is required");
}
int min = IntStream.of(input).min().getAsInt();
int max = IntStream.of(input).max().getAsInt();
if (min < 0 || max > k) {
throw new IllegalArgumentException("The input numbers should be between zero and " + k);
}
}
}
@@ -0,0 +1,25 @@
package com.baeldung.algorithms.inoutsort;
public class InOutSort {
public static int[] reverseInPlace(int A[]) {
int n = A.length;
for (int i = 0; i < n / 2; i++) {
int temp = A[i];
A[i] = A[n - 1 - i];
A[n - 1 - i] = temp;
}
return A;
}
public static int[] reverseOutOfPlace(int A[]) {
int n = A.length;
int[] B = new int[n];
for (int i = 0; i < n; i++) {
B[n - i - 1] = A[i];
}
return B;
}
}
@@ -0,0 +1,53 @@
package com.baeldung.algorithms.radixsort;
import java.util.Arrays;
public class RadixSort {
public static void sort(int numbers[]) {
int maximumNumber = findMaximumNumberIn(numbers);
int numberOfDigits = calculateNumberOfDigitsIn(maximumNumber);
int placeValue = 1;
while (numberOfDigits-- > 0) {
applyCountingSortOn(numbers, placeValue);
placeValue *= 10;
}
}
private static void applyCountingSortOn(int[] numbers, int placeValue) {
int range = 10; // radix or the base
int length = numbers.length;
int[] frequency = new int[range];
int[] sortedValues = new int[length];
for (int i = 0; i < length; i++) {
int digit = (numbers[i] / placeValue) % range;
frequency[digit]++;
}
for (int i = 1; i < range; i++) {
frequency[i] += frequency[i - 1];
}
for (int i = length - 1; i >= 0; i--) {
int digit = (numbers[i] / placeValue) % range;
sortedValues[frequency[digit] - 1] = numbers[i];
frequency[digit]--;
}
System.arraycopy(sortedValues, 0, numbers, 0, length);
}
private static int calculateNumberOfDigitsIn(int number) {
return (int) Math.log10(number) + 1; // valid only if number > 0
}
private static int findMaximumNumberIn(int[] arr) {
return Arrays.stream(arr).max().getAsInt();
}
}
@@ -1,4 +1,4 @@
package com.baeldung.algorithms.stringsortingbynumber;
package com.baeldung.algorithms.sort.bynumber;
import java.util.Comparator;
@@ -0,0 +1,32 @@
package com.baeldung.algorithms.counting;
import java.util.Arrays;
import static org.junit.jupiter.api.Assertions.assertArrayEquals;
import org.junit.jupiter.api.Test;
class CountingSortUnitTest {
@Test
void countElements_GivenAnArray_ShouldCalculateTheFrequencyArrayAsExpected() {
int k = 5;
int[] input = { 4, 3, 2, 5, 4, 3, 5, 1, 0, 2, 5 };
int[] c = CountingSort.countElements(input, k);
int[] expected = { 1, 2, 4, 6, 8, 11 };
assertArrayEquals(expected, c);
}
@Test
void sort_GivenAnArray_ShouldSortTheInputAsExpected() {
int k = 5;
int[] input = { 4, 3, 2, 5, 4, 3, 5, 1, 0, 2, 5 };
int[] sorted = CountingSort.sort(input, k);
// Our sorting algorithm and Java's should return the same result
Arrays.sort(input);
assertArrayEquals(input, sorted);
}
}
@@ -0,0 +1,23 @@
package com.baeldung.algorithms.inoutsort;
import static org.junit.Assert.*;
import static org.junit.Assert.assertArrayEquals;
import org.junit.Test;
public class InOutSortUnitTest {
@Test
public void givenArray_whenInPlaceSort_thenReversed() {
int[] input = {1, 2, 3, 4, 5, 6, 7};
int[] expected = {7, 6, 5, 4, 3, 2, 1};
assertArrayEquals("the two arrays are not equal", expected, InOutSort.reverseInPlace(input));
}
@Test
public void givenArray_whenOutOfPlaceSort_thenReversed() {
int[] input = {1, 2, 3, 4, 5, 6, 7};
int[] expected = {7, 6, 5, 4, 3, 2, 1};
assertArrayEquals("the two arrays are not equal", expected, InOutSort.reverseOutOfPlace(input));
}
}
@@ -0,0 +1,16 @@
package com.baeldung.algorithms.radixsort;
import static org.junit.Assert.assertArrayEquals;
import org.junit.Test;
public class RadixSortUnitTest {
@Test
public void givenUnsortedArray_whenRadixSort_thenArraySorted() {
int[] numbers = { 387, 468, 134, 123, 68, 221, 769, 37, 7 };
RadixSort.sort(numbers);
int[] numbersSorted = { 7, 37, 68, 123, 134, 221, 387, 468, 769 };
assertArrayEquals(numbersSorted, numbers);
}
}
@@ -1,6 +1,6 @@
package com.baeldung.algorithms.stringsortingbynumber;
package com.baeldung.algorithms.sort.bynumber;
import com.baeldung.algorithms.stringsortingbynumber.NaturalOrderComparators;
import com.baeldung.algorithms.sort.bynumber.NaturalOrderComparators;
import org.junit.Test;
import java.util.ArrayList;

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