Merge branch 'master' into Mercator

This commit is contained in:
Grigorios Dimopoulos
2018-11-05 11:09:23 +02:00
771 changed files with 72437 additions and 737 deletions

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package com.baeldung.algorithms;
import java.util.Scanner;
import com.baeldung.algorithms.slope_one.SlopeOne;
public class RunAlgorithm {
public static void main(String[] args) throws InstantiationException, IllegalAccessException {
Scanner in = new Scanner(System.in);
System.out.println("1 - Slope One");
System.out.println("2 - Dijkstra");
int decision = in.nextInt();
switch (decision) {
case 1:
SlopeOne.slopeOne(3);
break;
case 2:
System.out.println("Please run the DijkstraAlgorithmLongRunningUnitTest.");
break;
default:
System.out.println("Unknown option");
break;
}
in.close();
}
}

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package com.baeldung.algorithms.ga.dijkstra;
import java.util.HashSet;
import java.util.LinkedList;
import java.util.Map.Entry;
import java.util.Set;
public class Dijkstra {
public static Graph calculateShortestPathFromSource(Graph graph, Node source) {
source.setDistance(0);
Set<Node> settledNodes = new HashSet<>();
Set<Node> unsettledNodes = new HashSet<>();
unsettledNodes.add(source);
while (unsettledNodes.size() != 0) {
Node currentNode = getLowestDistanceNode(unsettledNodes);
unsettledNodes.remove(currentNode);
for (Entry<Node, Integer> adjacencyPair : currentNode.getAdjacentNodes().entrySet()) {
Node adjacentNode = adjacencyPair.getKey();
Integer edgeWeigh = adjacencyPair.getValue();
if (!settledNodes.contains(adjacentNode)) {
CalculateMinimumDistance(adjacentNode, edgeWeigh, currentNode);
unsettledNodes.add(adjacentNode);
}
}
settledNodes.add(currentNode);
}
return graph;
}
private static void CalculateMinimumDistance(Node evaluationNode, Integer edgeWeigh, Node sourceNode) {
Integer sourceDistance = sourceNode.getDistance();
if (sourceDistance + edgeWeigh < evaluationNode.getDistance()) {
evaluationNode.setDistance(sourceDistance + edgeWeigh);
LinkedList<Node> shortestPath = new LinkedList<>(sourceNode.getShortestPath());
shortestPath.add(sourceNode);
evaluationNode.setShortestPath(shortestPath);
}
}
private static Node getLowestDistanceNode(Set<Node> unsettledNodes) {
Node lowestDistanceNode = null;
int lowestDistance = Integer.MAX_VALUE;
for (Node node : unsettledNodes) {
int nodeDistance = node.getDistance();
if (nodeDistance < lowestDistance) {
lowestDistance = nodeDistance;
lowestDistanceNode = node;
}
}
return lowestDistanceNode;
}
}

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package com.baeldung.algorithms.ga.dijkstra;
import java.util.HashSet;
import java.util.Set;
public class Graph {
private Set<Node> nodes = new HashSet<>();
public void addNode(Node nodeA) {
nodes.add(nodeA);
}
public Set<Node> getNodes() {
return nodes;
}
public void setNodes(Set<Node> nodes) {
this.nodes = nodes;
}
}

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package com.baeldung.algorithms.ga.dijkstra;
import java.util.HashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
public class Node {
private String name;
private LinkedList<Node> shortestPath = new LinkedList<>();
private Integer distance = Integer.MAX_VALUE;
private Map<Node, Integer> adjacentNodes = new HashMap<>();
public Node(String name) {
this.name = name;
}
public void addDestination(Node destination, int distance) {
adjacentNodes.put(destination, distance);
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public Map<Node, Integer> getAdjacentNodes() {
return adjacentNodes;
}
public void setAdjacentNodes(Map<Node, Integer> adjacentNodes) {
this.adjacentNodes = adjacentNodes;
}
public Integer getDistance() {
return distance;
}
public void setDistance(Integer distance) {
this.distance = distance;
}
public List<Node> getShortestPath() {
return shortestPath;
}
public void setShortestPath(LinkedList<Node> shortestPath) {
this.shortestPath = shortestPath;
}
}

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package com.baeldung.algorithms.roundedup;
import java.util.Scanner;
public class RoundUpToHundred {
public static void main(String[] args) {
Scanner scanner = new Scanner(System.in);
double input = scanner.nextDouble();
scanner.close();
RoundUpToHundred.round(input);
}
static long round(double input) {
long i = (long) Math.ceil(input);
return ((i + 99) / 100) * 100;
};
}

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package com.baeldung.algorithms.slope_one;
import java.util.Arrays;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
import lombok.Data;
@Data
public class InputData {
protected static List<Item> items = Arrays.asList(new Item("Candy"), new Item("Drink"), new Item("Soda"), new Item("Popcorn"), new Item("Snacks"));
public static Map<User, HashMap<Item, Double>> initializeData(int numberOfUsers) {
Map<User, HashMap<Item, Double>> data = new HashMap<>();
HashMap<Item, Double> newUser;
Set<Item> newRecommendationSet;
for (int i = 0; i < numberOfUsers; i++) {
newUser = new HashMap<Item, Double>();
newRecommendationSet = new HashSet<>();
for (int j = 0; j < 3; j++) {
newRecommendationSet.add(items.get((int) (Math.random() * 5)));
}
for (Item item : newRecommendationSet) {
newUser.put(item, Math.random());
}
data.put(new User("User " + i), newUser);
}
return data;
}
}

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package com.baeldung.algorithms.slope_one;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
@Data
@NoArgsConstructor
@AllArgsConstructor
public class Item {
private String itemName;
}

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package com.baeldung.algorithms.slope_one;
import java.text.DecimalFormat;
import java.text.NumberFormat;
import java.util.HashMap;
import java.util.Map;
import java.util.Map.Entry;
/**
* Slope One algorithm implementation
*/
public class SlopeOne {
private static Map<Item, Map<Item, Double>> diff = new HashMap<>();
private static Map<Item, Map<Item, Integer>> freq = new HashMap<>();
private static Map<User, HashMap<Item, Double>> inputData;
private static Map<User, HashMap<Item, Double>> outputData = new HashMap<>();
public static void slopeOne(int numberOfUsers) {
inputData = InputData.initializeData(numberOfUsers);
System.out.println("Slope One - Before the Prediction\n");
buildDifferencesMatrix(inputData);
System.out.println("\nSlope One - With Predictions\n");
predict(inputData);
}
/**
* Based on the available data, calculate the relationships between the
* items and number of occurences
*
* @param data
* existing user data and their items' ratings
*/
private static void buildDifferencesMatrix(Map<User, HashMap<Item, Double>> data) {
for (HashMap<Item, Double> user : data.values()) {
for (Entry<Item, Double> e : user.entrySet()) {
if (!diff.containsKey(e.getKey())) {
diff.put(e.getKey(), new HashMap<Item, Double>());
freq.put(e.getKey(), new HashMap<Item, Integer>());
}
for (Entry<Item, Double> e2 : user.entrySet()) {
int oldCount = 0;
if (freq.get(e.getKey()).containsKey(e2.getKey())) {
oldCount = freq.get(e.getKey()).get(e2.getKey()).intValue();
}
double oldDiff = 0.0;
if (diff.get(e.getKey()).containsKey(e2.getKey())) {
oldDiff = diff.get(e.getKey()).get(e2.getKey()).doubleValue();
}
double observedDiff = e.getValue() - e2.getValue();
freq.get(e.getKey()).put(e2.getKey(), oldCount + 1);
diff.get(e.getKey()).put(e2.getKey(), oldDiff + observedDiff);
}
}
}
for (Item j : diff.keySet()) {
for (Item i : diff.get(j).keySet()) {
double oldValue = diff.get(j).get(i).doubleValue();
int count = freq.get(j).get(i).intValue();
diff.get(j).put(i, oldValue / count);
}
}
printData(data);
}
/**
* Based on existing data predict all missing ratings. If prediction is not
* possible, the value will be equal to -1
*
* @param data
* existing user data and their items' ratings
*/
private static void predict(Map<User, HashMap<Item, Double>> data) {
HashMap<Item, Double> uPred = new HashMap<Item, Double>();
HashMap<Item, Integer> uFreq = new HashMap<Item, Integer>();
for (Item j : diff.keySet()) {
uFreq.put(j, 0);
uPred.put(j, 0.0);
}
for (Entry<User, HashMap<Item, Double>> e : data.entrySet()) {
for (Item j : e.getValue().keySet()) {
for (Item k : diff.keySet()) {
try {
double predictedValue = diff.get(k).get(j).doubleValue() + e.getValue().get(j).doubleValue();
double finalValue = predictedValue * freq.get(k).get(j).intValue();
uPred.put(k, uPred.get(k) + finalValue);
uFreq.put(k, uFreq.get(k) + freq.get(k).get(j).intValue());
} catch (NullPointerException e1) {
}
}
}
HashMap<Item, Double> clean = new HashMap<Item, Double>();
for (Item j : uPred.keySet()) {
if (uFreq.get(j) > 0) {
clean.put(j, uPred.get(j).doubleValue() / uFreq.get(j).intValue());
}
}
for (Item j : InputData.items) {
if (e.getValue().containsKey(j)) {
clean.put(j, e.getValue().get(j));
} else {
clean.put(j, -1.0);
}
}
outputData.put(e.getKey(), clean);
}
printData(outputData);
}
private static void printData(Map<User, HashMap<Item, Double>> data) {
for (User user : data.keySet()) {
System.out.println(user.getUsername() + ":");
print(data.get(user));
}
}
private static void print(HashMap<Item, Double> hashMap) {
NumberFormat formatter = new DecimalFormat("#0.000");
for (Item j : hashMap.keySet()) {
System.out.println(" " + j.getItemName() + " --> " + formatter.format(hashMap.get(j).doubleValue()));
}
}
}

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package com.baeldung.algorithms.slope_one;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
@Data
@NoArgsConstructor
@AllArgsConstructor
public class User {
private String username;
}

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package com.baeldung.algorithms;
import org.junit.Test;
import com.baeldung.algorithms.ga.dijkstra.Dijkstra;
import com.baeldung.algorithms.ga.dijkstra.Graph;
import com.baeldung.algorithms.ga.dijkstra.Node;
import java.util.Arrays;
import java.util.List;
import static org.junit.Assert.assertTrue;
public class DijkstraAlgorithmLongRunningUnitTest {
@Test
public void whenSPPSolved_thenCorrect() {
Node nodeA = new Node("A");
Node nodeB = new Node("B");
Node nodeC = new Node("C");
Node nodeD = new Node("D");
Node nodeE = new Node("E");
Node nodeF = new Node("F");
nodeA.addDestination(nodeB, 10);
nodeA.addDestination(nodeC, 15);
nodeB.addDestination(nodeD, 12);
nodeB.addDestination(nodeF, 15);
nodeC.addDestination(nodeE, 10);
nodeD.addDestination(nodeE, 2);
nodeD.addDestination(nodeF, 1);
nodeF.addDestination(nodeE, 5);
Graph graph = new Graph();
graph.addNode(nodeA);
graph.addNode(nodeB);
graph.addNode(nodeC);
graph.addNode(nodeD);
graph.addNode(nodeE);
graph.addNode(nodeF);
graph = Dijkstra.calculateShortestPathFromSource(graph, nodeA);
List<Node> shortestPathForNodeB = Arrays.asList(nodeA);
List<Node> shortestPathForNodeC = Arrays.asList(nodeA);
List<Node> shortestPathForNodeD = Arrays.asList(nodeA, nodeB);
List<Node> shortestPathForNodeE = Arrays.asList(nodeA, nodeB, nodeD);
List<Node> shortestPathForNodeF = Arrays.asList(nodeA, nodeB, nodeD);
for (Node node : graph.getNodes()) {
switch (node.getName()) {
case "B":
assertTrue(node
.getShortestPath()
.equals(shortestPathForNodeB));
break;
case "C":
assertTrue(node
.getShortestPath()
.equals(shortestPathForNodeC));
break;
case "D":
assertTrue(node
.getShortestPath()
.equals(shortestPathForNodeD));
break;
case "E":
assertTrue(node
.getShortestPath()
.equals(shortestPathForNodeE));
break;
case "F":
assertTrue(node
.getShortestPath()
.equals(shortestPathForNodeF));
break;
}
}
}
}

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package com.baeldung.algorithms.roundedup;
import static org.junit.Assert.assertEquals;
import org.junit.Test;
public class RoundUpToHundredUnitTest {
@Test
public void givenInput_whenRound_thenRoundUpToTheNearestHundred() {
assertEquals("Rounded up to hundred", 100, RoundUpToHundred.round(99));
assertEquals("Rounded up to three hundred ", 300, RoundUpToHundred.round(200.2));
assertEquals("Returns same rounded value", 400, RoundUpToHundred.round(400));
}
}