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[BAEL-9551] - Splitted algorithms into 4 modules

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This commit is contained in:
amit2103
2018-10-28 23:29:09 +05:30
parent c10101a9ac
commit 539ce3e787
164 changed files with 1735 additions and 1241 deletions
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algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/automata/FiniteStateMachine.java
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package com.baeldung.algorithms.automata;
/**
* Finite state machine.
*/
public interface FiniteStateMachine {
/**
* Follow a transition, switch the state of the machine.
* @param c Char.
* @return A new finite state machine with the new state.
*/
FiniteStateMachine switchState(final CharSequence c);
/**
* Is the current state a final one?
* @return true or false.
*/
boolean canStop();
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/automata/RtFiniteStateMachine.java
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package com.baeldung.algorithms.automata;
/**
* Default implementation of a finite state machine.
* This class is immutable and thread-safe.
*/
public final class RtFiniteStateMachine implements FiniteStateMachine {
/**
* Current state.
*/
private State current;
/**
* Ctor.
* @param initial Initial state of this machine.
*/
public RtFiniteStateMachine(final State initial) {
this.current = initial;
}
public FiniteStateMachine switchState(final CharSequence c) {
return new RtFiniteStateMachine(this.current.transit(c));
}
public boolean canStop() {
return this.current.isFinal();
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/automata/RtState.java
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package com.baeldung.algorithms.automata;
import java.util.ArrayList;
import java.util.List;
/**
* State in a finite state machine.
*/
public final class RtState implements State {
private List<Transition> transitions;
private boolean isFinal;
public RtState() {
this(false);
}
public RtState(final boolean isFinal) {
this.transitions = new ArrayList<>();
this.isFinal = isFinal;
}
public State transit(final CharSequence c) {
return transitions
.stream()
.filter(t -> t.isPossible(c))
.map(Transition::state)
.findAny()
.orElseThrow(() -> new IllegalArgumentException("Input not accepted: " + c));
}
public boolean isFinal() {
return this.isFinal;
}
@Override
public State with(Transition tr) {
this.transitions.add(tr);
return this;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/automata/RtTransition.java
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package com.baeldung.algorithms.automata;
/**
* Transition in finite state machine.
*/
public final class RtTransition implements Transition {
private String rule;
private State next;
/**
* Ctor.
* @param rule Rule that a character has to meet
* in order to get to the next state.
* @param next Next state.
*/
public RtTransition (String rule, State next) {
this.rule = rule;
this.next = next;
}
public State state() {
return this.next;
}
public boolean isPossible(CharSequence c) {
return this.rule.equalsIgnoreCase(String.valueOf(c));
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/automata/State.java
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package com.baeldung.algorithms.automata;
/**
* State. Part of a finite state machine.
*/
public interface State {
/**
* Add a Transition to this state.
* @param tr Given transition.
* @return Modified State.
*/
State with(final Transition tr);
/**
* Follow one of the transitions, to get
* to the next state.
* @param c Character.
* @return State.
* @throws IllegalStateException if the char is not accepted.
*/
State transit(final CharSequence c);
/**
* Can the automaton stop on this state?
* @return true or false
*/
boolean isFinal();
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/automata/Transition.java
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package com.baeldung.algorithms.automata;
/**
* Transition in a finite State machine.
*/
public interface Transition {
/**
* Is the transition possible with the given character?
* @param c char.
* @return true or false.
*/
boolean isPossible(final CharSequence c);
/**
* The state to which this transition leads.
* @return State.
*/
State state();
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/binarysearch/BinarySearch.java
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package com.baeldung.algorithms.binarysearch;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
public class BinarySearch {
public int runBinarySearchIteratively(int[] sortedArray, int key, int low, int high) {
int index = Integer.MAX_VALUE;
while (low <= high) {
int mid = (low + high) / 2;
if (sortedArray[mid] < key) {
low = mid + 1;
} else if (sortedArray[mid] > key) {
high = mid - 1;
} else if (sortedArray[mid] == key) {
index = mid;
break;
}
}
return index;
}
public int runBinarySearchRecursively(int[] sortedArray, int key, int low, int high) {
int middle = (low + high) / 2;
if (high < low) {
return -1;
}
if (key == sortedArray[middle]) {
return middle;
} else if (key < sortedArray[middle]) {
return runBinarySearchRecursively(sortedArray, key, low, middle - 1);
} else {
return runBinarySearchRecursively(sortedArray, key, middle + 1, high);
}
}
public int runBinarySearchUsingJavaArrays(int[] sortedArray, Integer key) {
int index = Arrays.binarySearch(sortedArray, key);
return index;
}
public int runBinarySearchUsingJavaCollections(List<Integer> sortedList, Integer key) {
int index = Collections.binarySearch(sortedList, key);
return index;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/hillclimbing/HillClimbing.java
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package com.baeldung.algorithms.hillclimbing;
import java.util.ArrayList;
import java.util.List;
import java.util.Objects;
import java.util.Optional;
import java.util.Stack;
public class HillClimbing {
public static void main(String[] args) {
HillClimbing hillClimbing = new HillClimbing();
String blockArr[] = { "B", "C", "D", "A" };
Stack<String> startState = hillClimbing.getStackWithValues(blockArr);
String goalBlockArr[] = { "A", "B", "C", "D" };
Stack<String> goalState = hillClimbing.getStackWithValues(goalBlockArr);
try {
List<State> solutionSequence = hillClimbing.getRouteWithHillClimbing(startState, goalState);
solutionSequence.forEach(HillClimbing::printEachStep);
} catch (Exception e) {
e.printStackTrace();
}
}
private static void printEachStep(State state) {
List<Stack<String>> stackList = state.getState();
System.out.println("----------------");
stackList.forEach(stack -> {
while (!stack.isEmpty()) {
System.out.println(stack.pop());
}
System.out.println(" ");
});
}
private Stack<String> getStackWithValues(String[] blocks) {
Stack<String> stack = new Stack<>();
for (String block : blocks)
stack.push(block);
return stack;
}
/**
* This method prepares path from init state to goal state
*/
public List<State> getRouteWithHillClimbing(Stack<String> initStateStack, Stack<String> goalStateStack) throws Exception {
List<Stack<String>> initStateStackList = new ArrayList<>();
initStateStackList.add(initStateStack);
int initStateHeuristics = getHeuristicsValue(initStateStackList, goalStateStack);
State initState = new State(initStateStackList, initStateHeuristics);
List<State> resultPath = new ArrayList<>();
resultPath.add(new State(initState));
State currentState = initState;
boolean noStateFound = false;
while (!currentState.getState()
.get(0)
.equals(goalStateStack) || noStateFound) {
noStateFound = true;
State nextState = findNextState(currentState, goalStateStack);
if (nextState != null) {
noStateFound = false;
currentState = nextState;
resultPath.add(new State(nextState));
}
}
return resultPath;
}
/**
* This method finds new state from current state based on goal and
* heuristics
*/
public State findNextState(State currentState, Stack<String> goalStateStack) {
List<Stack<String>> listOfStacks = currentState.getState();
int currentStateHeuristics = currentState.getHeuristics();
return listOfStacks.stream()
.map(stack -> {
return applyOperationsOnState(listOfStacks, stack, currentStateHeuristics, goalStateStack);
})
.filter(Objects::nonNull)
.findFirst()
.orElse(null);
}
/**
* This method applies operations on the current state to get a new state
*/
public State applyOperationsOnState(List<Stack<String>> listOfStacks, Stack<String> stack, int currentStateHeuristics, Stack<String> goalStateStack) {
State tempState;
List<Stack<String>> tempStackList = new ArrayList<>(listOfStacks);
String block = stack.pop();
if (stack.size() == 0)
tempStackList.remove(stack);
tempState = pushElementToNewStack(tempStackList, block, currentStateHeuristics, goalStateStack);
if (tempState == null) {
tempState = pushElementToExistingStacks(stack, tempStackList, block, currentStateHeuristics, goalStateStack);
}
if (tempState == null)
stack.push(block);
return tempState;
}
/**
* Operation to be applied on a state in order to find new states. This
* operation pushes an element into a new stack
*/
private State pushElementToNewStack(List<Stack<String>> currentStackList, String block, int currentStateHeuristics, Stack<String> goalStateStack) {
State newState = null;
Stack<String> newStack = new Stack<>();
newStack.push(block);
currentStackList.add(newStack);
int newStateHeuristics = getHeuristicsValue(currentStackList, goalStateStack);
if (newStateHeuristics > currentStateHeuristics) {
newState = new State(currentStackList, newStateHeuristics);
} else {
currentStackList.remove(newStack);
}
return newState;
}
/**
* Operation to be applied on a state in order to find new states. This
* operation pushes an element into one of the other stacks to explore new
* states
*/
private State pushElementToExistingStacks(Stack currentStack, List<Stack<String>> currentStackList, String block, int currentStateHeuristics, Stack<String> goalStateStack) {
Optional<State> newState = currentStackList.stream()
.filter(stack -> stack != currentStack)
.map(stack -> {
return pushElementToStack(stack, block, currentStackList, currentStateHeuristics, goalStateStack);
})
.filter(Objects::nonNull)
.findFirst();
return newState.orElse(null);
}
/**
* This method pushes a block to the stack and returns new state if its closer to goal
*/
private State pushElementToStack(Stack stack, String block, List<Stack<String>> currentStackList, int currentStateHeuristics, Stack<String> goalStateStack) {
stack.push(block);
int newStateHeuristics = getHeuristicsValue(currentStackList, goalStateStack);
if (newStateHeuristics > currentStateHeuristics) {
return new State(currentStackList, newStateHeuristics);
}
stack.pop();
return null;
}
/**
* This method returns heuristics value for given state with respect to goal
* state
*/
public int getHeuristicsValue(List<Stack<String>> currentState, Stack<String> goalStateStack) {
Integer heuristicValue;
heuristicValue = currentState.stream()
.mapToInt(stack -> {
return getHeuristicsValueForStack(stack, currentState, goalStateStack);
})
.sum();
return heuristicValue;
}
/**
* This method returns heuristics value for a particular stack
*/
public int getHeuristicsValueForStack(Stack<String> stack, List<Stack<String>> currentState, Stack<String> goalStateStack) {
int stackHeuristics = 0;
boolean isPositioneCorrect = true;
int goalStartIndex = 0;
for (String currentBlock : stack) {
if (isPositioneCorrect && currentBlock.equals(goalStateStack.get(goalStartIndex))) {
stackHeuristics += goalStartIndex;
} else {
stackHeuristics -= goalStartIndex;
isPositioneCorrect = false;
}
goalStartIndex++;
}
return stackHeuristics;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/hillclimbing/State.java
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package com.baeldung.algorithms.hillclimbing;
import java.util.ArrayList;
import java.util.List;
import java.util.Stack;
public class State {
private List<Stack<String>> state;
private int heuristics;
public State(List<Stack<String>> state) {
this.state = state;
}
State(List<Stack<String>> state, int heuristics) {
this.state = state;
this.heuristics = heuristics;
}
State(State state) {
if (state != null) {
this.state = new ArrayList<>();
for (Stack s : state.getState()) {
Stack s1;
s1 = (Stack) s.clone();
this.state.add(s1);
}
this.heuristics = state.getHeuristics();
}
}
public List<Stack<String>> getState() {
return state;
}
public int getHeuristics() {
return heuristics;
}
public void setHeuristics(int heuristics) {
this.heuristics = heuristics;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/kthlargest/FindKthLargest.java
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package com.baeldung.algorithms.kthlargest;
import java.util.Arrays;
import java.util.Collections;
import java.util.stream.IntStream;
public class FindKthLargest {
public int findKthLargestBySorting(Integer[] arr, int k) {
Arrays.sort(arr);
int targetIndex = arr.length - k;
return arr[targetIndex];
}
public int findKthLargestBySortingDesc(Integer[] arr, int k) {
Arrays.sort(arr, Collections.reverseOrder());
return arr[k - 1];
}
public int findKthElementByQuickSelect(Integer[] arr, int left, int right, int k) {
if (k >= 0 && k <= right - left + 1) {
int pos = partition(arr, left, right);
if (pos - left == k) {
return arr[pos];
}
if (pos - left > k) {
return findKthElementByQuickSelect(arr, left, pos - 1, k);
}
return findKthElementByQuickSelect(arr, pos + 1, right, k - pos + left - 1);
}
return 0;
}
public int findKthElementByQuickSelectWithIterativePartition(Integer[] arr, int left, int right, int k) {
if (k >= 0 && k <= right - left + 1) {
int pos = partitionIterative(arr, left, right);
if (pos - left == k) {
return arr[pos];
}
if (pos - left > k) {
return findKthElementByQuickSelectWithIterativePartition(arr, left, pos - 1, k);
}
return findKthElementByQuickSelectWithIterativePartition(arr, pos + 1, right, k - pos + left - 1);
}
return 0;
}
private int partition(Integer[] arr, int left, int right) {
int pivot = arr[right];
Integer[] leftArr;
Integer[] rightArr;
leftArr = IntStream.range(left, right)
.filter(i -> arr[i] < pivot)
.map(i -> arr[i])
.boxed()
.toArray(Integer[]::new);
rightArr = IntStream.range(left, right)
.filter(i -> arr[i] > pivot)
.map(i -> arr[i])
.boxed()
.toArray(Integer[]::new);
int leftArraySize = leftArr.length;
System.arraycopy(leftArr, 0, arr, left, leftArraySize);
arr[leftArraySize + left] = pivot;
System.arraycopy(rightArr, 0, arr, left + leftArraySize + 1, rightArr.length);
return left + leftArraySize;
}
private int partitionIterative(Integer[] arr, int left, int right) {
int pivot = arr[right], i = left;
for (int j = left; j <= right - 1; j++) {
if (arr[j] <= pivot) {
swap(arr, i, j);
i++;
}
}
swap(arr, i, right);
return i;
}
public int findKthElementByRandomizedQuickSelect(Integer[] arr, int left, int right, int k) {
if (k >= 0 && k <= right - left + 1) {
int pos = randomPartition(arr, left, right);
if (pos - left == k) {
return arr[pos];
}
if (pos - left > k) {
return findKthElementByRandomizedQuickSelect(arr, left, pos - 1, k);
}
return findKthElementByRandomizedQuickSelect(arr, pos + 1, right, k - pos + left - 1);
}
return 0;
}
private int randomPartition(Integer arr[], int left, int right) {
int n = right - left + 1;
int pivot = (int) (Math.random() * n);
swap(arr, left + pivot, right);
return partition(arr, left, right);
}
private void swap(Integer[] arr, int n1, int n2) {
int temp = arr[n2];
arr[n2] = arr[n1];
arr[n1] = temp;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/linesintersection/LinesIntersectionService.java
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package com.baeldung.algorithms.linesintersection;
import java.awt.Point;
import java.util.Optional;
public class LinesIntersectionService {
public Optional<Point> calculateIntersectionPoint(double m1, double b1, double m2, double b2) {
if (m1 == m2) {
return Optional.empty();
}
double x = (b2 - b1) / (m1 - m2);
double y = m1 * x + b1;
Point point = new Point();
point.setLocation(x, y);
return Optional.of(point);
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/mcts/montecarlo/MonteCarloTreeSearch.java
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package com.baeldung.algorithms.mcts.montecarlo;
import java.util.List;
import com.baeldung.algorithms.mcts.tictactoe.Board;
import com.baeldung.algorithms.mcts.tree.Node;
import com.baeldung.algorithms.mcts.tree.Tree;
public class MonteCarloTreeSearch {
private static final int WIN_SCORE = 10;
private int level;
private int opponent;
public MonteCarloTreeSearch() {
this.level = 3;
}
public int getLevel() {
return level;
}
public void setLevel(int level) {
this.level = level;
}
private int getMillisForCurrentLevel() {
return 2 * (this.level - 1) + 1;
}
public Board findNextMove(Board board, int playerNo) {
long start = System.currentTimeMillis();
long end = start + 60 * getMillisForCurrentLevel();
opponent = 3 - playerNo;
Tree tree = new Tree();
Node rootNode = tree.getRoot();
rootNode.getState().setBoard(board);
rootNode.getState().setPlayerNo(opponent);
while (System.currentTimeMillis() < end) {
// Phase 1 - Selection
Node promisingNode = selectPromisingNode(rootNode);
// Phase 2 - Expansion
if (promisingNode.getState().getBoard().checkStatus() == Board.IN_PROGRESS)
expandNode(promisingNode);
// Phase 3 - Simulation
Node nodeToExplore = promisingNode;
if (promisingNode.getChildArray().size() > 0) {
nodeToExplore = promisingNode.getRandomChildNode();
}
int playoutResult = simulateRandomPlayout(nodeToExplore);
// Phase 4 - Update
backPropogation(nodeToExplore, playoutResult);
}
Node winnerNode = rootNode.getChildWithMaxScore();
tree.setRoot(winnerNode);
return winnerNode.getState().getBoard();
}
private Node selectPromisingNode(Node rootNode) {
Node node = rootNode;
while (node.getChildArray().size() != 0) {
node = UCT.findBestNodeWithUCT(node);
}
return node;
}
private void expandNode(Node node) {
List<State> possibleStates = node.getState().getAllPossibleStates();
possibleStates.forEach(state -> {
Node newNode = new Node(state);
newNode.setParent(node);
newNode.getState().setPlayerNo(node.getState().getOpponent());
node.getChildArray().add(newNode);
});
}
private void backPropogation(Node nodeToExplore, int playerNo) {
Node tempNode = nodeToExplore;
while (tempNode != null) {
tempNode.getState().incrementVisit();
if (tempNode.getState().getPlayerNo() == playerNo)
tempNode.getState().addScore(WIN_SCORE);
tempNode = tempNode.getParent();
}
}
private int simulateRandomPlayout(Node node) {
Node tempNode = new Node(node);
State tempState = tempNode.getState();
int boardStatus = tempState.getBoard().checkStatus();
if (boardStatus == opponent) {
tempNode.getParent().getState().setWinScore(Integer.MIN_VALUE);
return boardStatus;
}
while (boardStatus == Board.IN_PROGRESS) {
tempState.togglePlayer();
tempState.randomPlay();
boardStatus = tempState.getBoard().checkStatus();
}
return boardStatus;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/mcts/montecarlo/State.java
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package com.baeldung.algorithms.mcts.montecarlo;
import java.util.ArrayList;
import java.util.List;
import com.baeldung.algorithms.mcts.tictactoe.Board;
import com.baeldung.algorithms.mcts.tictactoe.Position;
public class State {
private Board board;
private int playerNo;
private int visitCount;
private double winScore;
public State() {
board = new Board();
}
public State(State state) {
this.board = new Board(state.getBoard());
this.playerNo = state.getPlayerNo();
this.visitCount = state.getVisitCount();
this.winScore = state.getWinScore();
}
public State(Board board) {
this.board = new Board(board);
}
Board getBoard() {
return board;
}
void setBoard(Board board) {
this.board = board;
}
int getPlayerNo() {
return playerNo;
}
void setPlayerNo(int playerNo) {
this.playerNo = playerNo;
}
int getOpponent() {
return 3 - playerNo;
}
public int getVisitCount() {
return visitCount;
}
public void setVisitCount(int visitCount) {
this.visitCount = visitCount;
}
double getWinScore() {
return winScore;
}
void setWinScore(double winScore) {
this.winScore = winScore;
}
public List<State> getAllPossibleStates() {
List<State> possibleStates = new ArrayList<>();
List<Position> availablePositions = this.board.getEmptyPositions();
availablePositions.forEach(p -> {
State newState = new State(this.board);
newState.setPlayerNo(3 - this.playerNo);
newState.getBoard().performMove(newState.getPlayerNo(), p);
possibleStates.add(newState);
});
return possibleStates;
}
void incrementVisit() {
this.visitCount++;
}
void addScore(double score) {
if (this.winScore != Integer.MIN_VALUE)
this.winScore += score;
}
void randomPlay() {
List<Position> availablePositions = this.board.getEmptyPositions();
int totalPossibilities = availablePositions.size();
int selectRandom = (int) (Math.random() * totalPossibilities);
this.board.performMove(this.playerNo, availablePositions.get(selectRandom));
}
void togglePlayer() {
this.playerNo = 3 - this.playerNo;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/mcts/montecarlo/UCT.java
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package com.baeldung.algorithms.mcts.montecarlo;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
import com.baeldung.algorithms.mcts.tree.Node;
public class UCT {
public static double uctValue(int totalVisit, double nodeWinScore, int nodeVisit) {
if (nodeVisit == 0) {
return Integer.MAX_VALUE;
}
return (nodeWinScore / (double) nodeVisit) + 1.41 * Math.sqrt(Math.log(totalVisit) / (double) nodeVisit);
}
static Node findBestNodeWithUCT(Node node) {
int parentVisit = node.getState().getVisitCount();
return Collections.max(
node.getChildArray(),
Comparator.comparing(c -> uctValue(parentVisit, c.getState().getWinScore(), c.getState().getVisitCount())));
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/mcts/tictactoe/Board.java
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package com.baeldung.algorithms.mcts.tictactoe;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
public class Board {
int[][] boardValues;
int totalMoves;
public static final int DEFAULT_BOARD_SIZE = 3;
public static final int IN_PROGRESS = -1;
public static final int DRAW = 0;
public static final int P1 = 1;
public static final int P2 = 2;
public Board() {
boardValues = new int[DEFAULT_BOARD_SIZE][DEFAULT_BOARD_SIZE];
}
public Board(int boardSize) {
boardValues = new int[boardSize][boardSize];
}
public Board(int[][] boardValues) {
this.boardValues = boardValues;
}
public Board(int[][] boardValues, int totalMoves) {
this.boardValues = boardValues;
this.totalMoves = totalMoves;
}
public Board(Board board) {
int boardLength = board.getBoardValues().length;
this.boardValues = new int[boardLength][boardLength];
int[][] boardValues = board.getBoardValues();
int n = boardValues.length;
for (int i = 0; i < n; i++) {
int m = boardValues[i].length;
for (int j = 0; j < m; j++) {
this.boardValues[i][j] = boardValues[i][j];
}
}
}
public void performMove(int player, Position p) {
this.totalMoves++;
boardValues[p.getX()][p.getY()] = player;
}
public int[][] getBoardValues() {
return boardValues;
}
public void setBoardValues(int[][] boardValues) {
this.boardValues = boardValues;
}
public int checkStatus() {
int boardSize = boardValues.length;
int maxIndex = boardSize - 1;
int[] diag1 = new int[boardSize];
int[] diag2 = new int[boardSize];
for (int i = 0; i < boardSize; i++) {
int[] row = boardValues[i];
int[] col = new int[boardSize];
for (int j = 0; j < boardSize; j++) {
col[j] = boardValues[j][i];
}
int checkRowForWin = checkForWin(row);
if(checkRowForWin!=0)
return checkRowForWin;
int checkColForWin = checkForWin(col);
if(checkColForWin!=0)
return checkColForWin;
diag1[i] = boardValues[i][i];
diag2[i] = boardValues[maxIndex - i][i];
}
int checkDia1gForWin = checkForWin(diag1);
if(checkDia1gForWin!=0)
return checkDia1gForWin;
int checkDiag2ForWin = checkForWin(diag2);
if(checkDiag2ForWin!=0)
return checkDiag2ForWin;
if (getEmptyPositions().size() > 0)
return IN_PROGRESS;
else
return DRAW;
}
private int checkForWin(int[] row) {
boolean isEqual = true;
int size = row.length;
int previous = row[0];
for (int i = 0; i < size; i++) {
if (previous != row[i]) {
isEqual = false;
break;
}
previous = row[i];
}
if(isEqual)
return previous;
else
return 0;
}
public void printBoard() {
int size = this.boardValues.length;
for (int i = 0; i < size; i++) {
for (int j = 0; j < size; j++) {
System.out.print(boardValues[i][j] + " ");
}
System.out.println();
}
}
public List<Position> getEmptyPositions() {
int size = this.boardValues.length;
List<Position> emptyPositions = new ArrayList<>();
for (int i = 0; i < size; i++) {
for (int j = 0; j < size; j++) {
if (boardValues[i][j] == 0)
emptyPositions.add(new Position(i, j));
}
}
return emptyPositions;
}
public void printStatus() {
switch (this.checkStatus()) {
case P1:
System.out.println("Player 1 wins");
break;
case P2:
System.out.println("Player 2 wins");
break;
case DRAW:
System.out.println("Game Draw");
break;
case IN_PROGRESS:
System.out.println("Game In Progress");
break;
}
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/mcts/tictactoe/Position.java
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package com.baeldung.algorithms.mcts.tictactoe;
public class Position {
int x;
int y;
public Position() {
}
public Position(int x, int y) {
this.x = x;
this.y = y;
}
public int getX() {
return x;
}
public void setX(int x) {
this.x = x;
}
public int getY() {
return y;
}
public void setY(int y) {
this.y = y;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/mcts/tree/Node.java
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package com.baeldung.algorithms.mcts.tree;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
import com.baeldung.algorithms.mcts.montecarlo.State;
public class Node {
State state;
Node parent;
List<Node> childArray;
public Node() {
this.state = new State();
childArray = new ArrayList<>();
}
public Node(State state) {
this.state = state;
childArray = new ArrayList<>();
}
public Node(State state, Node parent, List<Node> childArray) {
this.state = state;
this.parent = parent;
this.childArray = childArray;
}
public Node(Node node) {
this.childArray = new ArrayList<>();
this.state = new State(node.getState());
if (node.getParent() != null)
this.parent = node.getParent();
List<Node> childArray = node.getChildArray();
for (Node child : childArray) {
this.childArray.add(new Node(child));
}
}
public State getState() {
return state;
}
public void setState(State state) {
this.state = state;
}
public Node getParent() {
return parent;
}
public void setParent(Node parent) {
this.parent = parent;
}
public List<Node> getChildArray() {
return childArray;
}
public void setChildArray(List<Node> childArray) {
this.childArray = childArray;
}
public Node getRandomChildNode() {
int noOfPossibleMoves = this.childArray.size();
int selectRandom = (int) (Math.random() * noOfPossibleMoves);
return this.childArray.get(selectRandom);
}
public Node getChildWithMaxScore() {
return Collections.max(this.childArray, Comparator.comparing(c -> {
return c.getState().getVisitCount();
}));
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/mcts/tree/Tree.java
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package com.baeldung.algorithms.mcts.tree;
public class Tree {
Node root;
public Tree() {
root = new Node();
}
public Tree(Node root) {
this.root = root;
}
public Node getRoot() {
return root;
}
public void setRoot(Node root) {
this.root = root;
}
public void addChild(Node parent, Node child) {
parent.getChildArray().add(child);
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/middleelementlookup/MiddleElementLookup.java
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package com.baeldung.algorithms.middleelementlookup;
import java.util.LinkedList;
import java.util.Optional;
public class MiddleElementLookup {
public static Optional<String> findMiddleElementLinkedList(LinkedList<String> linkedList) {
if (linkedList == null || linkedList.isEmpty()) {
return Optional.empty();
}
return Optional.ofNullable(linkedList.get((linkedList.size() - 1) / 2));
}
public static Optional<String> findMiddleElementFromHead(Node head) {
if (head == null) {
return Optional.empty();
}
// calculate the size of the list
Node current = head;
int size = 1;
while (current.hasNext()) {
current = current.next();
size++;
}
// iterate till the middle element
current = head;
for (int i = 0; i < (size - 1) / 2; i++) {
current = current.next();
}
return Optional.ofNullable(current.data());
}
public static Optional<String> findMiddleElementFromHead1PassRecursively(Node head) {
if (head == null) {
return Optional.empty();
}
MiddleAuxRecursion middleAux = new MiddleAuxRecursion();
findMiddleRecursively(head, middleAux);
return Optional.ofNullable(middleAux.middle.data());
}
private static void findMiddleRecursively(Node node, MiddleAuxRecursion middleAux) {
if (node == null) {
// reached the end
middleAux.length = middleAux.length / 2;
return;
}
middleAux.length++;
findMiddleRecursively(node.next(), middleAux);
if (middleAux.length == 0) {
// found the middle
middleAux.middle = node;
}
middleAux.length--;
}
public static Optional<String> findMiddleElementFromHead1PassIteratively(Node head) {
if (head == null) {
return Optional.empty();
}
Node slowPointer = head;
Node fastPointer = head;
while (fastPointer.hasNext() && fastPointer.next()
.hasNext()) {
fastPointer = fastPointer.next()
.next();
slowPointer = slowPointer.next();
}
return Optional.ofNullable(slowPointer.data());
}
private static class MiddleAuxRecursion {
Node middle;
int length = 0;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/middleelementlookup/Node.java
+34
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package com.baeldung.algorithms.middleelementlookup;
public class Node {
private Node next;
private String data;
public Node(String data) {
this.data = data;
}
public String data() {
return data;
}
public void setData(String data) {
this.data = data;
}
public boolean hasNext() {
return next != null;
}
public Node next() {
return next;
}
public void setNext(Node next) {
this.next = next;
}
public String toString() {
return this.data;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/minimax/GameOfBones.java
+14
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package com.baeldung.algorithms.minimax;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.IntStream;
class GameOfBones {
static List<Integer> getPossibleStates(int noOfBonesInHeap) {
return IntStream.rangeClosed(1, 3).boxed()
.map(i -> noOfBonesInHeap - i)
.filter(newHeapCount -> newHeapCount >= 0)
.collect(Collectors.toList());
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/minimax/MiniMax.java
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package com.baeldung.algorithms.minimax;
import java.util.Comparator;
import java.util.List;
import java.util.NoSuchElementException;
public class MiniMax {
private Tree tree;
public Tree getTree() {
return tree;
}
public void constructTree(int noOfBones) {
tree = new Tree();
Node root = new Node(noOfBones, true);
tree.setRoot(root);
constructTree(root);
}
private void constructTree(Node parentNode) {
List<Integer> listofPossibleHeaps = GameOfBones.getPossibleStates(parentNode.getNoOfBones());
boolean isChildMaxPlayer = !parentNode.isMaxPlayer();
listofPossibleHeaps.forEach(n -> {
Node newNode = new Node(n, isChildMaxPlayer);
parentNode.addChild(newNode);
if (newNode.getNoOfBones() > 0) {
constructTree(newNode);
}
});
}
public boolean checkWin() {
Node root = tree.getRoot();
checkWin(root);
return root.getScore() == 1;
}
private void checkWin(Node node) {
List<Node> children = node.getChildren();
boolean isMaxPlayer = node.isMaxPlayer();
children.forEach(child -> {
if (child.getNoOfBones() == 0) {
child.setScore(isMaxPlayer ? 1 : -1);
} else {
checkWin(child);
}
});
Node bestChild = findBestChild(isMaxPlayer, children);
node.setScore(bestChild.getScore());
}
private Node findBestChild(boolean isMaxPlayer, List<Node> children) {
Comparator<Node> byScoreComparator = Comparator.comparing(Node::getScore);
return children.stream()
.max(isMaxPlayer ? byScoreComparator : byScoreComparator.reversed())
.orElseThrow(NoSuchElementException::new);
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/minimax/Node.java
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package com.baeldung.algorithms.minimax;
import java.util.ArrayList;
import java.util.List;
public class Node {
private int noOfBones;
private boolean isMaxPlayer;
private int score;
private List<Node> children;
public Node(int noOfBones, boolean isMaxPlayer) {
this.noOfBones = noOfBones;
this.isMaxPlayer = isMaxPlayer;
children = new ArrayList<>();
}
int getNoOfBones() {
return noOfBones;
}
boolean isMaxPlayer() {
return isMaxPlayer;
}
int getScore() {
return score;
}
void setScore(int score) {
this.score = score;
}
List<Node> getChildren() {
return children;
}
void addChild(Node newNode) {
children.add(newNode);
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/minimax/Tree.java
+16
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package com.baeldung.algorithms.minimax;
public class Tree {
private Node root;
Tree() {
}
Node getRoot() {
return root;
}
void setRoot(Node root) {
this.root = root;
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/multiswarm/Constants.java
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package com.baeldung.algorithms.multiswarm;
/**
* Constants used by the Multi-swarm optimization algorithms.
*
* @author Donato Rimenti
*
*/
public class Constants {
/**
* The inertia factor encourages a particle to continue moving in its
* current direction.
*/
public static final double INERTIA_FACTOR = 0.729;
/**
* The cognitive weight encourages a particle to move toward its historical
* best-known position.
*/
public static final double COGNITIVE_WEIGHT = 1.49445;
/**
* The social weight encourages a particle to move toward the best-known
* position found by any of the particle’s swarm-mates.
*/
public static final double SOCIAL_WEIGHT = 1.49445;
/**
* The global weight encourages a particle to move toward the best-known
* position found by any particle in any swarm.
*/
public static final double GLOBAL_WEIGHT = 0.3645;
/**
* Upper bound for the random generation. We use it to reduce the
* computation time since we can rawly estimate it.
*/
public static final int PARTICLE_UPPER_BOUND = 10000000;
/**
* Private constructor for utility class.
*/
private Constants() {
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/multiswarm/FitnessFunction.java
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package com.baeldung.algorithms.multiswarm;
/**
* Interface for a fitness function, used to decouple the main algorithm logic
* from the specific problem solution.
*
* @author Donato Rimenti
*
*/
public interface FitnessFunction {
/**
* Returns the fitness of a particle given its position.
*
* @param particlePosition
* the position of the particle
* @return the fitness of the particle
*/
public double getFitness(long[] particlePosition);
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/multiswarm/Multiswarm.java
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package com.baeldung.algorithms.multiswarm;
import java.util.Arrays;
import java.util.Random;
/**
* Represents a collection of {@link Swarm}.
*
* @author Donato Rimenti
*
*/
public class Multiswarm {
/**
* The swarms managed by this multiswarm.
*/
private Swarm[] swarms;
/**
* The best position found within all the {@link #swarms}.
*/
private long[] bestPosition;
/**
* The best fitness score found within all the {@link #swarms}.
*/
private double bestFitness = Double.NEGATIVE_INFINITY;
/**
* A random generator.
*/
private Random random = new Random();
/**
* The fitness function used to determine how good is a particle.
*/
private FitnessFunction fitnessFunction;
/**
* Instantiates a new Multiswarm.
*
* @param numSwarms
* the number of {@link #swarms}
* @param particlesPerSwarm
* the number of particle for each {@link #swarms}
* @param fitnessFunction
* the {@link #fitnessFunction}
*/
public Multiswarm(int numSwarms, int particlesPerSwarm, FitnessFunction fitnessFunction) {
this.fitnessFunction = fitnessFunction;
this.swarms = new Swarm[numSwarms];
for (int i = 0; i < numSwarms; i++) {
swarms[i] = new Swarm(particlesPerSwarm);
}
}
/**
* Main loop of the algorithm. Iterates all particles of all
* {@link #swarms}. For each particle, computes the new fitness and checks
* if a new best position has been found among itself, the swarm and all the
* swarms and finally updates the particle position and speed.
*/
public void mainLoop() {
for (Swarm swarm : swarms) {
for (Particle particle : swarm.getParticles()) {
long[] particleOldPosition = particle.getPosition().clone();
// Calculate the particle fitness.
particle.setFitness(fitnessFunction.getFitness(particleOldPosition));
// Check if a new best position has been found for the particle
// itself, within the swarm and the multiswarm.
if (particle.getFitness() > particle.getBestFitness()) {
particle.setBestFitness(particle.getFitness());
particle.setBestPosition(particleOldPosition);
if (particle.getFitness() > swarm.getBestFitness()) {
swarm.setBestFitness(particle.getFitness());
swarm.setBestPosition(particleOldPosition);
if (swarm.getBestFitness() > bestFitness) {
bestFitness = swarm.getBestFitness();
bestPosition = swarm.getBestPosition().clone();
}
}
}
// Updates the particle position by adding the speed to the
// actual position.
long[] position = particle.getPosition();
long[] speed = particle.getSpeed();
position[0] += speed[0];
position[1] += speed[1];
// Updates the particle speed.
speed[0] = getNewParticleSpeedForIndex(particle, swarm, 0);
speed[1] = getNewParticleSpeedForIndex(particle, swarm, 1);
}
}
}
/**
* Computes a new speed for a given particle of a given swarm on a given
* axis. The new speed is computed using the formula:
*
* <pre>
* ({@link Constants#INERTIA_FACTOR} * {@link Particle#getSpeed()}) +
* (({@link Constants#COGNITIVE_WEIGHT} * random(0,1)) * ({@link Particle#getBestPosition()} - {@link Particle#getPosition()})) +
* (({@link Constants#SOCIAL_WEIGHT} * random(0,1)) * ({@link Swarm#getBestPosition()} - {@link Particle#getPosition()})) +
* (({@link Constants#GLOBAL_WEIGHT} * random(0,1)) * ({@link #bestPosition} - {@link Particle#getPosition()}))
* </pre>
*
* @param particle
* the particle whose new speed needs to be computed
* @param swarm
* the swarm which contains the particle
* @param index
* the index of the particle axis whose speeds needs to be
* computed
* @return the new speed of the particle passed on the given axis
*/
private int getNewParticleSpeedForIndex(Particle particle, Swarm swarm, int index) {
return (int) ((Constants.INERTIA_FACTOR * particle.getSpeed()[index])
+ (randomizePercentage(Constants.COGNITIVE_WEIGHT)
* (particle.getBestPosition()[index] - particle.getPosition()[index]))
+ (randomizePercentage(Constants.SOCIAL_WEIGHT)
* (swarm.getBestPosition()[index] - particle.getPosition()[index]))
+ (randomizePercentage(Constants.GLOBAL_WEIGHT)
* (bestPosition[index] - particle.getPosition()[index])));
}
/**
* Returns a random number between 0 and the value passed as argument.
*
* @param value
* the value to randomize
* @return a random value between 0 and the one passed as argument
*/
private double randomizePercentage(double value) {
return random.nextDouble() * value;
}
/**
* Gets the {@link #bestPosition}.
*
* @return the {@link #bestPosition}
*/
public long[] getBestPosition() {
return bestPosition;
}
/**
* Gets the {@link #bestFitness}.
*
* @return the {@link #bestFitness}
*/
public double getBestFitness() {
return bestFitness;
}
/*
* (non-Javadoc)
*
* @see java.lang.Object#hashCode()
*/
@Override
public int hashCode() {
final int prime = 31;
int result = 1;
long temp;
temp = Double.doubleToLongBits(bestFitness);
result = prime * result + (int) (temp ^ (temp >>> 32));
result = prime * result + Arrays.hashCode(bestPosition);
result = prime * result + ((fitnessFunction == null) ? 0 : fitnessFunction.hashCode());
result = prime * result + ((random == null) ? 0 : random.hashCode());
result = prime * result + Arrays.hashCode(swarms);
return result;
}
/*
* (non-Javadoc)
*
* @see java.lang.Object#equals(java.lang.Object)
*/
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (getClass() != obj.getClass())
return false;
Multiswarm other = (Multiswarm) obj;
if (Double.doubleToLongBits(bestFitness) != Double.doubleToLongBits(other.bestFitness))
return false;
if (!Arrays.equals(bestPosition, other.bestPosition))
return false;
if (fitnessFunction == null) {
if (other.fitnessFunction != null)
return false;
} else if (!fitnessFunction.equals(other.fitnessFunction))
return false;
if (random == null) {
if (other.random != null)
return false;
} else if (!random.equals(other.random))
return false;
if (!Arrays.equals(swarms, other.swarms))
return false;
return true;
}
/*
* (non-Javadoc)
*
* @see java.lang.Object#toString()
*/
@Override
public String toString() {
return "Multiswarm [swarms=" + Arrays.toString(swarms) + ", bestPosition=" + Arrays.toString(bestPosition)
+ ", bestFitness=" + bestFitness + ", random=" + random + ", fitnessFunction=" + fitnessFunction + "]";
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/multiswarm/Particle.java
+204
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package com.baeldung.algorithms.multiswarm;
import java.util.Arrays;
/**
* Represents a particle, the basic component of a {@link Swarm}.
*
* @author Donato Rimenti
*
*/
public class Particle {
/**
* The current position of this particle.
*/
private long[] position;
/**
* The speed of this particle.
*/
private long[] speed;
/**
* The fitness of this particle for the current position.
*/
private double fitness;
/**
* The best position found by this particle.
*/
private long[] bestPosition;
/**
* The best fitness found by this particle.
*/
private double bestFitness = Double.NEGATIVE_INFINITY;
/**
* Instantiates a new Particle.
*
* @param initialPosition
* the initial {@link #position}
* @param initialSpeed
* the initial {@link #speed}
*/
public Particle(long[] initialPosition, long[] initialSpeed) {
this.position = initialPosition;
this.speed = initialSpeed;
}
/**
* Gets the {@link #position}.
*
* @return the {@link #position}
*/
public long[] getPosition() {
return position;
}
/**
* Gets the {@link #speed}.
*
* @return the {@link #speed}
*/
public long[] getSpeed() {
return speed;
}
/**
* Gets the {@link #fitness}.
*
* @return the {@link #fitness}
*/
public double getFitness() {
return fitness;
}
/**
* Gets the {@link #bestPosition}.
*
* @return the {@link #bestPosition}
*/
public long[] getBestPosition() {
return bestPosition;
}
/**
* Gets the {@link #bestFitness}.
*
* @return the {@link #bestFitness}
*/
public double getBestFitness() {
return bestFitness;
}
/**
* Sets the {@link #position}.
*
* @param position
* the new {@link #position}
*/
public void setPosition(long[] position) {
this.position = position;
}
/**
* Sets the {@link #speed}.
*
* @param speed
* the new {@link #speed}
*/
public void setSpeed(long[] speed) {
this.speed = speed;
}
/**
* Sets the {@link #fitness}.
*
* @param fitness
* the new {@link #fitness}
*/
public void setFitness(double fitness) {
this.fitness = fitness;
}
/**
* Sets the {@link #bestPosition}.
*
* @param bestPosition
* the new {@link #bestPosition}
*/
public void setBestPosition(long[] bestPosition) {
this.bestPosition = bestPosition;
}
/**
* Sets the {@link #bestFitness}.
*
* @param bestFitness
* the new {@link #bestFitness}
*/
public void setBestFitness(double bestFitness) {
this.bestFitness = bestFitness;
}
/*
* (non-Javadoc)
*
* @see java.lang.Object#hashCode()
*/
@Override
public int hashCode() {
final int prime = 31;
int result = 1;
long temp;
temp = Double.doubleToLongBits(bestFitness);
result = prime * result + (int) (temp ^ (temp >>> 32));
result = prime * result + Arrays.hashCode(bestPosition);
temp = Double.doubleToLongBits(fitness);
result = prime * result + (int) (temp ^ (temp >>> 32));
result = prime * result + Arrays.hashCode(position);
result = prime * result + Arrays.hashCode(speed);
return result;
}
/*
* (non-Javadoc)
*
* @see java.lang.Object#equals(java.lang.Object)
*/
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (getClass() != obj.getClass())
return false;
Particle other = (Particle) obj;
if (Double.doubleToLongBits(bestFitness) != Double.doubleToLongBits(other.bestFitness))
return false;
if (!Arrays.equals(bestPosition, other.bestPosition))
return false;
if (Double.doubleToLongBits(fitness) != Double.doubleToLongBits(other.fitness))
return false;
if (!Arrays.equals(position, other.position))
return false;
if (!Arrays.equals(speed, other.speed))
return false;
return true;
}
/*
* (non-Javadoc)
*
* @see java.lang.Object#toString()
*/
@Override
public String toString() {
return "Particle [position=" + Arrays.toString(position) + ", speed=" + Arrays.toString(speed) + ", fitness="
+ fitness + ", bestPosition=" + Arrays.toString(bestPosition) + ", bestFitness=" + bestFitness + "]";
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/multiswarm/Swarm.java
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package com.baeldung.algorithms.multiswarm;
import java.util.Arrays;
import java.util.Random;
/**
* Represents a collection of {@link Particle}.
*
* @author Donato Rimenti
*
*/
public class Swarm {
/**
* The particles of this swarm.
*/
private Particle[] particles;
/**
* The best position found within the particles of this swarm.
*/
private long[] bestPosition;
/**
* The best fitness score found within the particles of this swarm.
*/
private double bestFitness = Double.NEGATIVE_INFINITY;
/**
* A random generator.
*/
private Random random = new Random();
/**
* Instantiates a new Swarm.
*
* @param numParticles
* the number of particles of the swarm
*/
public Swarm(int numParticles) {
particles = new Particle[numParticles];
for (int i = 0; i < numParticles; i++) {
long[] initialParticlePosition = { random.nextInt(Constants.PARTICLE_UPPER_BOUND),
random.nextInt(Constants.PARTICLE_UPPER_BOUND) };
long[] initialParticleSpeed = { random.nextInt(Constants.PARTICLE_UPPER_BOUND),
random.nextInt(Constants.PARTICLE_UPPER_BOUND) };
particles[i] = new Particle(initialParticlePosition, initialParticleSpeed);
}
}
/**
* Gets the {@link #particles}.
*
* @return the {@link #particles}
*/
public Particle[] getParticles() {
return particles;
}
/**
* Gets the {@link #bestPosition}.
*
* @return the {@link #bestPosition}
*/
public long[] getBestPosition() {
return bestPosition;
}
/**
* Gets the {@link #bestFitness}.
*
* @return the {@link #bestFitness}
*/
public double getBestFitness() {
return bestFitness;
}
/**
* Sets the {@link #bestPosition}.
*
* @param bestPosition
* the new {@link #bestPosition}
*/
public void setBestPosition(long[] bestPosition) {
this.bestPosition = bestPosition;
}
/**
* Sets the {@link #bestFitness}.
*
* @param bestFitness
* the new {@link #bestFitness}
*/
public void setBestFitness(double bestFitness) {
this.bestFitness = bestFitness;
}
/*
* (non-Javadoc)
*
* @see java.lang.Object#hashCode()
*/
@Override
public int hashCode() {
final int prime = 31;
int result = 1;
long temp;
temp = Double.doubleToLongBits(bestFitness);
result = prime * result + (int) (temp ^ (temp >>> 32));
result = prime * result + Arrays.hashCode(bestPosition);
result = prime * result + Arrays.hashCode(particles);
result = prime * result + ((random == null) ? 0 : random.hashCode());
return result;
}
/*
* (non-Javadoc)
*
* @see java.lang.Object#equals(java.lang.Object)
*/
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (getClass() != obj.getClass())
return false;
Swarm other = (Swarm) obj;
if (Double.doubleToLongBits(bestFitness) != Double.doubleToLongBits(other.bestFitness))
return false;
if (!Arrays.equals(bestPosition, other.bestPosition))
return false;
if (!Arrays.equals(particles, other.particles))
return false;
if (random == null) {
if (other.random != null)
return false;
} else if (!random.equals(other.random))
return false;
return true;
}
/*
* (non-Javadoc)
*
* @see java.lang.Object#toString()
*/
@Override
public String toString() {
return "Swarm [particles=" + Arrays.toString(particles) + ", bestPosition=" + Arrays.toString(bestPosition)
+ ", bestFitness=" + bestFitness + ", random=" + random + "]";
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/string/EnglishAlphabetLetters.java
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package com.baeldung.algorithms.string;
public class EnglishAlphabetLetters {
public static boolean checkStringForAllTheLetters(String input) {
boolean[] visited = new boolean[26];
int index = 0;
for (int id = 0; id < input.length(); id++) {
if ('a' <= input.charAt(id) && input.charAt(id) <= 'z') {
index = input.charAt(id) - 'a';
} else if ('A' <= input.charAt(id) && input.charAt(id) <= 'Z') {
index = input.charAt(id) - 'A';
}
visited[index] = true;
}
for (int id = 0; id < 26; id++) {
if (!visited[id]) {
return false;
}
}
return true;
}
public static boolean checkStringForAllLetterUsingStream(String input) {
long c = input.toLowerCase().chars().filter(ch -> ch >= 'a' && ch <= 'z').distinct().count();
return c == 26;
}
public static void main(String[] args) {
checkStringForAllLetterUsingStream("intit");
}
}
algorithms-miscellaneous-1/src/main/java/com/baeldung/algorithms/string/search/StringSearchAlgorithms.java
Executable
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package com.baeldung.algorithms.string.search;
import java.math.BigInteger;
import java.util.Random;
public class StringSearchAlgorithms {
public static long getBiggerPrime(int m) {
BigInteger prime = BigInteger.probablePrime(getNumberOfBits(m) + 1, new Random());
return prime.longValue();
}
public static long getLowerPrime(long number) {
BigInteger prime = BigInteger.probablePrime(getNumberOfBits(number) - 1, new Random());
return prime.longValue();
}
private static int getNumberOfBits(final int number) {
return Integer.SIZE - Integer.numberOfLeadingZeros(number);
}
private static int getNumberOfBits(final long number) {
return Long.SIZE - Long.numberOfLeadingZeros(number);
}
public static int simpleTextSearch(char[] pattern, char[] text) {
int patternSize = pattern.length;
int textSize = text.length;
int i = 0;
while ((i + patternSize) <= textSize) {
int j = 0;
while (text[i + j] == pattern[j]) {
j += 1;
if (j >= patternSize)
return i;
}
i += 1;
}
return -1;
}
public static int RabinKarpMethod(char[] pattern, char[] text) {
int patternSize = pattern.length; // m
int textSize = text.length; // n
long prime = getBiggerPrime(patternSize);
long r = 1;
for (int i = 0; i < patternSize - 1; i++) {
r *= 2;
r = r % prime;
}
long[] t = new long[textSize];
t[0] = 0;
long pfinger = 0;
for (int j = 0; j < patternSize; j++) {
t[0] = (2 * t[0] + text[j]) % prime;
pfinger = (2 * pfinger + pattern[j]) % prime;
}
int i = 0;
boolean passed = false;
int diff = textSize - patternSize;
for (i = 0; i <= diff; i++) {
if (t[i] == pfinger) {
passed = true;
for (int k = 0; k < patternSize; k++) {
if (text[i + k] != pattern[k]) {
passed = false;
break;
}
}
if (passed) {
return i;
}
}
if (i < diff) {
long value = 2 * (t[i] - r * text[i]) + text[i + patternSize];
t[i + 1] = ((value % prime) + prime) % prime;
}
}
return -1;
}
public static int KnuthMorrisPrattSearch(char[] pattern, char[] text) {
int patternSize = pattern.length; // m
int textSize = text.length; // n
int i = 0, j = 0;
int[] shift = KnuthMorrisPrattShift(pattern);
while ((i + patternSize) <= textSize) {
while (text[i + j] == pattern[j]) {
j += 1;
if (j >= patternSize)
return i;
}
if (j > 0) {
i += shift[j - 1];
j = Math.max(j - shift[j - 1], 0);
} else {
i++;
j = 0;
}
}
return -1;
}
public static int[] KnuthMorrisPrattShift(char[] pattern) {
int patternSize = pattern.length;
int[] shift = new int[patternSize];
shift[0] = 1;
int i = 1, j = 0;
while ((i + j) < patternSize) {
if (pattern[i + j] == pattern[j]) {
shift[i + j] = i;
j++;
} else {
if (j == 0)
shift[i] = i + 1;
if (j > 0) {
i = i + shift[j - 1];
j = Math.max(j - shift[j - 1], 0);
} else {
i = i + 1;
j = 0;
}
}
}
return shift;
}
public static int BoyerMooreHorspoolSimpleSearch(char[] pattern, char[] text) {
int patternSize = pattern.length;
int textSize = text.length;
int i = 0, j = 0;
while ((i + patternSize) <= textSize) {
j = patternSize - 1;
while (text[i + j] == pattern[j]) {
j--;
if (j < 0)
return i;
}
i++;
}
return -1;
}
public static int BoyerMooreHorspoolSearch(char[] pattern, char[] text) {
int shift[] = new int[256];
for (int k = 0; k < 256; k++) {
shift[k] = pattern.length;
}
for (int k = 0; k < pattern.length - 1; k++) {
shift[pattern[k]] = pattern.length - 1 - k;
}
int i = 0, j = 0;
while ((i + pattern.length) <= text.length) {
j = pattern.length - 1;
while (text[i + j] == pattern[j]) {
j -= 1;
if (j < 0)
return i;
}
i = i + shift[text[i + pattern.length - 1]];
}
return -1;
}
}
algorithms-miscellaneous-1/src/main/resources/logback.xml
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<?xml version="1.0" encoding="UTF-8"?>
<configuration>
<appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender">
<encoder>
<pattern>%d{HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n
</pattern>
</encoder>
</appender>
<root level="INFO">
<appender-ref ref="STDOUT" />
</root>
</configuration>
algorithms-miscellaneous-1/src/main/resources/maze/maze1.txt
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S ########
# #
# ### ## #
# # # #
# # # # #
# ## #####
# # #
# # # # #
##### ####
# # E
# # # #
##########
algorithms-miscellaneous-1/src/main/resources/maze/maze2.txt
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S ##########################
# # # #
# # #### ############### #
# # # # # #
# # #### # # ###############
# # # # # # #
# # # #### ### ########### #
# # # # # #
# ################## #
######### # # # # #
# # #### # ####### # #
# # ### ### # # # # #
# # ## # ##### # #
##### ####### # # # # #
# # ## ## #### # #
# ##### ####### # #
# # ############
####### ######### # #
# # ######## #
# ####### ###### ## # E
# # # ## #
############################