[BAEL-9551] - Splitted algorithms into 4 modules
This commit is contained in:
@@ -0,0 +1,20 @@
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package com.baeldung.algorithms.automata;
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/**
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* Finite state machine.
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*/
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public interface FiniteStateMachine {
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/**
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* Follow a transition, switch the state of the machine.
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* @param c Char.
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* @return A new finite state machine with the new state.
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*/
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FiniteStateMachine switchState(final CharSequence c);
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/**
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* Is the current state a final one?
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* @return true or false.
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*/
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boolean canStop();
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}
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@@ -0,0 +1,30 @@
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package com.baeldung.algorithms.automata;
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/**
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* Default implementation of a finite state machine.
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* This class is immutable and thread-safe.
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*/
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public final class RtFiniteStateMachine implements FiniteStateMachine {
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/**
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* Current state.
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*/
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private State current;
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/**
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* Ctor.
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* @param initial Initial state of this machine.
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*/
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public RtFiniteStateMachine(final State initial) {
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this.current = initial;
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}
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public FiniteStateMachine switchState(final CharSequence c) {
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return new RtFiniteStateMachine(this.current.transit(c));
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}
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public boolean canStop() {
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return this.current.isFinal();
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}
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}
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@@ -0,0 +1,42 @@
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package com.baeldung.algorithms.automata;
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import java.util.ArrayList;
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import java.util.List;
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/**
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* State in a finite state machine.
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*/
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public final class RtState implements State {
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private List<Transition> transitions;
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private boolean isFinal;
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public RtState() {
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this(false);
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}
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public RtState(final boolean isFinal) {
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this.transitions = new ArrayList<>();
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this.isFinal = isFinal;
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}
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public State transit(final CharSequence c) {
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return transitions
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.stream()
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.filter(t -> t.isPossible(c))
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.map(Transition::state)
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.findAny()
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.orElseThrow(() -> new IllegalArgumentException("Input not accepted: " + c));
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}
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public boolean isFinal() {
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return this.isFinal;
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}
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@Override
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public State with(Transition tr) {
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this.transitions.add(tr);
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return this;
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}
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}
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@@ -0,0 +1,31 @@
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package com.baeldung.algorithms.automata;
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/**
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* Transition in finite state machine.
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*/
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public final class RtTransition implements Transition {
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private String rule;
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private State next;
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/**
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* Ctor.
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* @param rule Rule that a character has to meet
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* in order to get to the next state.
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* @param next Next state.
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*/
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public RtTransition (String rule, State next) {
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this.rule = rule;
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this.next = next;
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}
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public State state() {
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return this.next;
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}
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public boolean isPossible(CharSequence c) {
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return this.rule.equalsIgnoreCase(String.valueOf(c));
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}
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}
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@@ -0,0 +1,29 @@
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package com.baeldung.algorithms.automata;
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/**
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* State. Part of a finite state machine.
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*/
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public interface State {
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/**
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* Add a Transition to this state.
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* @param tr Given transition.
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* @return Modified State.
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*/
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State with(final Transition tr);
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/**
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* Follow one of the transitions, to get
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* to the next state.
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* @param c Character.
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* @return State.
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* @throws IllegalStateException if the char is not accepted.
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*/
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State transit(final CharSequence c);
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/**
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* Can the automaton stop on this state?
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* @return true or false
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*/
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boolean isFinal();
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}
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@@ -0,0 +1,20 @@
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package com.baeldung.algorithms.automata;
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/**
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* Transition in a finite State machine.
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*/
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public interface Transition {
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/**
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* Is the transition possible with the given character?
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* @param c char.
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* @return true or false.
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*/
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boolean isPossible(final CharSequence c);
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/**
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* The state to which this transition leads.
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* @return State.
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*/
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State state();
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}
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@@ -0,0 +1,55 @@
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package com.baeldung.algorithms.binarysearch;
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import java.util.Arrays;
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import java.util.Collections;
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import java.util.List;
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public class BinarySearch {
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public int runBinarySearchIteratively(int[] sortedArray, int key, int low, int high) {
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int index = Integer.MAX_VALUE;
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while (low <= high) {
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int mid = (low + high) / 2;
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if (sortedArray[mid] < key) {
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low = mid + 1;
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} else if (sortedArray[mid] > key) {
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high = mid - 1;
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} else if (sortedArray[mid] == key) {
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index = mid;
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break;
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}
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}
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return index;
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}
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public int runBinarySearchRecursively(int[] sortedArray, int key, int low, int high) {
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int middle = (low + high) / 2;
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if (high < low) {
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return -1;
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}
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if (key == sortedArray[middle]) {
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return middle;
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} else if (key < sortedArray[middle]) {
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return runBinarySearchRecursively(sortedArray, key, low, middle - 1);
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} else {
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return runBinarySearchRecursively(sortedArray, key, middle + 1, high);
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}
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}
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public int runBinarySearchUsingJavaArrays(int[] sortedArray, Integer key) {
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int index = Arrays.binarySearch(sortedArray, key);
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return index;
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}
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public int runBinarySearchUsingJavaCollections(List<Integer> sortedList, Integer key) {
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int index = Collections.binarySearch(sortedList, key);
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return index;
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}
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}
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@@ -0,0 +1,189 @@
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package com.baeldung.algorithms.hillclimbing;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.Objects;
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import java.util.Optional;
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import java.util.Stack;
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public class HillClimbing {
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public static void main(String[] args) {
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HillClimbing hillClimbing = new HillClimbing();
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String blockArr[] = { "B", "C", "D", "A" };
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Stack<String> startState = hillClimbing.getStackWithValues(blockArr);
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String goalBlockArr[] = { "A", "B", "C", "D" };
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Stack<String> goalState = hillClimbing.getStackWithValues(goalBlockArr);
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try {
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List<State> solutionSequence = hillClimbing.getRouteWithHillClimbing(startState, goalState);
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solutionSequence.forEach(HillClimbing::printEachStep);
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} catch (Exception e) {
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e.printStackTrace();
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}
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}
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private static void printEachStep(State state) {
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List<Stack<String>> stackList = state.getState();
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System.out.println("----------------");
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stackList.forEach(stack -> {
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while (!stack.isEmpty()) {
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System.out.println(stack.pop());
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}
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System.out.println(" ");
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});
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}
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private Stack<String> getStackWithValues(String[] blocks) {
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Stack<String> stack = new Stack<>();
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for (String block : blocks)
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stack.push(block);
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return stack;
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}
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/**
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* This method prepares path from init state to goal state
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*/
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public List<State> getRouteWithHillClimbing(Stack<String> initStateStack, Stack<String> goalStateStack) throws Exception {
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List<Stack<String>> initStateStackList = new ArrayList<>();
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initStateStackList.add(initStateStack);
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int initStateHeuristics = getHeuristicsValue(initStateStackList, goalStateStack);
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State initState = new State(initStateStackList, initStateHeuristics);
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List<State> resultPath = new ArrayList<>();
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resultPath.add(new State(initState));
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State currentState = initState;
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boolean noStateFound = false;
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while (!currentState.getState()
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.get(0)
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.equals(goalStateStack) || noStateFound) {
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noStateFound = true;
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State nextState = findNextState(currentState, goalStateStack);
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if (nextState != null) {
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noStateFound = false;
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currentState = nextState;
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resultPath.add(new State(nextState));
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}
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}
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return resultPath;
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}
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/**
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* This method finds new state from current state based on goal and
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* heuristics
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*/
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public State findNextState(State currentState, Stack<String> goalStateStack) {
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List<Stack<String>> listOfStacks = currentState.getState();
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int currentStateHeuristics = currentState.getHeuristics();
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return listOfStacks.stream()
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.map(stack -> {
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return applyOperationsOnState(listOfStacks, stack, currentStateHeuristics, goalStateStack);
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})
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.filter(Objects::nonNull)
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.findFirst()
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.orElse(null);
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}
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/**
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* This method applies operations on the current state to get a new state
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*/
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public State applyOperationsOnState(List<Stack<String>> listOfStacks, Stack<String> stack, int currentStateHeuristics, Stack<String> goalStateStack) {
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State tempState;
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List<Stack<String>> tempStackList = new ArrayList<>(listOfStacks);
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String block = stack.pop();
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if (stack.size() == 0)
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tempStackList.remove(stack);
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tempState = pushElementToNewStack(tempStackList, block, currentStateHeuristics, goalStateStack);
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if (tempState == null) {
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tempState = pushElementToExistingStacks(stack, tempStackList, block, currentStateHeuristics, goalStateStack);
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}
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if (tempState == null)
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stack.push(block);
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return tempState;
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}
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/**
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* Operation to be applied on a state in order to find new states. This
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* operation pushes an element into a new stack
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*/
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private State pushElementToNewStack(List<Stack<String>> currentStackList, String block, int currentStateHeuristics, Stack<String> goalStateStack) {
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State newState = null;
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Stack<String> newStack = new Stack<>();
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newStack.push(block);
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currentStackList.add(newStack);
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int newStateHeuristics = getHeuristicsValue(currentStackList, goalStateStack);
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if (newStateHeuristics > currentStateHeuristics) {
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newState = new State(currentStackList, newStateHeuristics);
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} else {
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currentStackList.remove(newStack);
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}
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return newState;
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}
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/**
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* Operation to be applied on a state in order to find new states. This
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* operation pushes an element into one of the other stacks to explore new
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* states
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*/
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private State pushElementToExistingStacks(Stack currentStack, List<Stack<String>> currentStackList, String block, int currentStateHeuristics, Stack<String> goalStateStack) {
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Optional<State> newState = currentStackList.stream()
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.filter(stack -> stack != currentStack)
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.map(stack -> {
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return pushElementToStack(stack, block, currentStackList, currentStateHeuristics, goalStateStack);
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})
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.filter(Objects::nonNull)
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.findFirst();
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return newState.orElse(null);
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}
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/**
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* This method pushes a block to the stack and returns new state if its closer to goal
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*/
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private State pushElementToStack(Stack stack, String block, List<Stack<String>> currentStackList, int currentStateHeuristics, Stack<String> goalStateStack) {
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stack.push(block);
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int newStateHeuristics = getHeuristicsValue(currentStackList, goalStateStack);
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if (newStateHeuristics > currentStateHeuristics) {
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return new State(currentStackList, newStateHeuristics);
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}
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stack.pop();
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return null;
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}
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/**
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* This method returns heuristics value for given state with respect to goal
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* state
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*/
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public int getHeuristicsValue(List<Stack<String>> currentState, Stack<String> goalStateStack) {
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Integer heuristicValue;
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heuristicValue = currentState.stream()
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.mapToInt(stack -> {
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return getHeuristicsValueForStack(stack, currentState, goalStateStack);
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})
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.sum();
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return heuristicValue;
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}
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/**
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* This method returns heuristics value for a particular stack
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*/
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public int getHeuristicsValueForStack(Stack<String> stack, List<Stack<String>> currentState, Stack<String> goalStateStack) {
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int stackHeuristics = 0;
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boolean isPositioneCorrect = true;
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int goalStartIndex = 0;
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for (String currentBlock : stack) {
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if (isPositioneCorrect && currentBlock.equals(goalStateStack.get(goalStartIndex))) {
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stackHeuristics += goalStartIndex;
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} else {
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stackHeuristics -= goalStartIndex;
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isPositioneCorrect = false;
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}
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goalStartIndex++;
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}
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return stackHeuristics;
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}
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}
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@@ -0,0 +1,43 @@
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package com.baeldung.algorithms.hillclimbing;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.Stack;
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public class State {
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private List<Stack<String>> state;
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private int heuristics;
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public State(List<Stack<String>> state) {
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this.state = state;
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}
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State(List<Stack<String>> state, int heuristics) {
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this.state = state;
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this.heuristics = heuristics;
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}
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State(State state) {
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if (state != null) {
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this.state = new ArrayList<>();
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for (Stack s : state.getState()) {
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Stack s1;
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s1 = (Stack) s.clone();
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this.state.add(s1);
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}
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this.heuristics = state.getHeuristics();
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}
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}
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public List<Stack<String>> getState() {
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return state;
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}
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public int getHeuristics() {
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return heuristics;
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}
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public void setHeuristics(int heuristics) {
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this.heuristics = heuristics;
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}
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}
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@@ -0,0 +1,111 @@
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package com.baeldung.algorithms.kthlargest;
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import java.util.Arrays;
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import java.util.Collections;
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import java.util.stream.IntStream;
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public class FindKthLargest {
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public int findKthLargestBySorting(Integer[] arr, int k) {
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Arrays.sort(arr);
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int targetIndex = arr.length - k;
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return arr[targetIndex];
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}
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public int findKthLargestBySortingDesc(Integer[] arr, int k) {
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Arrays.sort(arr, Collections.reverseOrder());
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return arr[k - 1];
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}
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public int findKthElementByQuickSelect(Integer[] arr, int left, int right, int k) {
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if (k >= 0 && k <= right - left + 1) {
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int pos = partition(arr, left, right);
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if (pos - left == k) {
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return arr[pos];
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}
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if (pos - left > k) {
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return findKthElementByQuickSelect(arr, left, pos - 1, k);
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}
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return findKthElementByQuickSelect(arr, pos + 1, right, k - pos + left - 1);
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}
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return 0;
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}
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public int findKthElementByQuickSelectWithIterativePartition(Integer[] arr, int left, int right, int k) {
|
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if (k >= 0 && k <= right - left + 1) {
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int pos = partitionIterative(arr, left, right);
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if (pos - left == k) {
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return arr[pos];
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}
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if (pos - left > k) {
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return findKthElementByQuickSelectWithIterativePartition(arr, left, pos - 1, k);
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}
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return findKthElementByQuickSelectWithIterativePartition(arr, pos + 1, right, k - pos + left - 1);
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}
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return 0;
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}
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private int partition(Integer[] arr, int left, int right) {
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int pivot = arr[right];
|
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Integer[] leftArr;
|
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Integer[] rightArr;
|
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|
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leftArr = IntStream.range(left, right)
|
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.filter(i -> arr[i] < pivot)
|
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.map(i -> arr[i])
|
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.boxed()
|
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.toArray(Integer[]::new);
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|
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rightArr = IntStream.range(left, right)
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.filter(i -> arr[i] > pivot)
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.map(i -> arr[i])
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.boxed()
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.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;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,21 @@
|
||||
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);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,109 @@
|
||||
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;
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,97 @@
|
||||
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;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,24 @@
|
||||
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())));
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,155 @@
|
||||
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;
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,31 @@
|
||||
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;
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,78 @@
|
||||
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();
|
||||
}));
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,26 @@
|
||||
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);
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,88 @@
|
||||
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;
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,34 @@
|
||||
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;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,14 @@
|
||||
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());
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,60 @@
|
||||
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);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,42 @@
|
||||
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);
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,16 @@
|
||||
package com.baeldung.algorithms.minimax;
|
||||
|
||||
public class Tree {
|
||||
private Node root;
|
||||
|
||||
Tree() {
|
||||
}
|
||||
|
||||
Node getRoot() {
|
||||
return root;
|
||||
}
|
||||
|
||||
void setRoot(Node root) {
|
||||
this.root = root;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,47 @@
|
||||
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() {
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,21 @@
|
||||
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);
|
||||
|
||||
}
|
||||
@@ -0,0 +1,227 @@
|
||||
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 + "]";
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,204 @@
|
||||
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 + "]";
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,155 @@
|
||||
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 + "]";
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,35 @@
|
||||
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");
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,194 @@
|
||||
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;
|
||||
}
|
||||
}
|
||||
13
algorithms-miscellaneous-1/src/main/resources/logback.xml
Normal file
13
algorithms-miscellaneous-1/src/main/resources/logback.xml
Normal file
@@ -0,0 +1,13 @@
|
||||
<?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>
|
||||
12
algorithms-miscellaneous-1/src/main/resources/maze/maze1.txt
Normal file
12
algorithms-miscellaneous-1/src/main/resources/maze/maze1.txt
Normal file
@@ -0,0 +1,12 @@
|
||||
S ########
|
||||
# #
|
||||
# ### ## #
|
||||
# # # #
|
||||
# # # # #
|
||||
# ## #####
|
||||
# # #
|
||||
# # # # #
|
||||
##### ####
|
||||
# # E
|
||||
# # # #
|
||||
##########
|
||||
22
algorithms-miscellaneous-1/src/main/resources/maze/maze2.txt
Normal file
22
algorithms-miscellaneous-1/src/main/resources/maze/maze2.txt
Normal file
@@ -0,0 +1,22 @@
|
||||
S ##########################
|
||||
# # # #
|
||||
# # #### ############### #
|
||||
# # # # # #
|
||||
# # #### # # ###############
|
||||
# # # # # # #
|
||||
# # # #### ### ########### #
|
||||
# # # # # #
|
||||
# ################## #
|
||||
######### # # # # #
|
||||
# # #### # ####### # #
|
||||
# # ### ### # # # # #
|
||||
# # ## # ##### # #
|
||||
##### ####### # # # # #
|
||||
# # ## ## #### # #
|
||||
# ##### ####### # #
|
||||
# # ############
|
||||
####### ######### # #
|
||||
# # ######## #
|
||||
# ####### ###### ## # E
|
||||
# # # ## #
|
||||
############################
|
||||
@@ -0,0 +1,58 @@
|
||||
package com.baeldung.algorithms;
|
||||
|
||||
import com.baeldung.algorithms.hillclimbing.HillClimbing;
|
||||
import com.baeldung.algorithms.hillclimbing.State;
|
||||
import org.junit.Before;
|
||||
import org.junit.Test;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Stack;
|
||||
|
||||
import static org.junit.Assert.assertEquals;
|
||||
import static org.junit.Assert.assertNotNull;
|
||||
import static org.junit.Assert.assertTrue;
|
||||
|
||||
public class HillClimbingAlgorithmUnitTest {
|
||||
private Stack<String> initStack;
|
||||
private Stack<String> goalStack;
|
||||
|
||||
@Before
|
||||
public void initStacks() {
|
||||
String blockArr[] = { "B", "C", "D", "A" };
|
||||
String goalBlockArr[] = { "A", "B", "C", "D" };
|
||||
initStack = new Stack<>();
|
||||
for (String block : blockArr)
|
||||
initStack.push(block);
|
||||
goalStack = new Stack<>();
|
||||
for (String block : goalBlockArr)
|
||||
goalStack.push(block);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenInitAndGoalState_whenGetPathWithHillClimbing_thenPathFound() {
|
||||
HillClimbing hillClimbing = new HillClimbing();
|
||||
|
||||
List<State> path;
|
||||
try {
|
||||
path = hillClimbing.getRouteWithHillClimbing(initStack, goalStack);
|
||||
assertNotNull(path);
|
||||
assertEquals(path.get(path.size() - 1)
|
||||
.getState()
|
||||
.get(0), goalStack);
|
||||
} catch (Exception e) {
|
||||
e.printStackTrace();
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenCurrentState_whenFindNextState_thenBetterHeuristics() {
|
||||
HillClimbing hillClimbing = new HillClimbing();
|
||||
List<Stack<String>> initList = new ArrayList<>();
|
||||
initList.add(initStack);
|
||||
State currentState = new State(initList);
|
||||
currentState.setHeuristics(hillClimbing.getHeuristicsValue(initList, goalStack));
|
||||
State nextState = hillClimbing.findNextState(currentState, goalStack);
|
||||
assertTrue(nextState.getHeuristics() > currentState.getHeuristics());
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,118 @@
|
||||
package com.baeldung.algorithms;
|
||||
|
||||
import com.baeldung.algorithms.middleelementlookup.MiddleElementLookup;
|
||||
import com.baeldung.algorithms.middleelementlookup.Node;
|
||||
import org.junit.Test;
|
||||
|
||||
import java.util.LinkedList;
|
||||
|
||||
import static org.junit.Assert.assertEquals;
|
||||
import static org.junit.Assert.assertFalse;
|
||||
|
||||
public class MiddleElementLookupUnitTest {
|
||||
|
||||
@Test
|
||||
public void whenFindingMiddleLinkedList_thenMiddleFound() {
|
||||
assertEquals("3", MiddleElementLookup
|
||||
.findMiddleElementLinkedList(createLinkedList(5))
|
||||
.get());
|
||||
assertEquals("2", MiddleElementLookup
|
||||
.findMiddleElementLinkedList(createLinkedList(4))
|
||||
.get());
|
||||
}
|
||||
|
||||
@Test
|
||||
public void whenFindingMiddleFromHead_thenMiddleFound() {
|
||||
assertEquals("3", MiddleElementLookup
|
||||
.findMiddleElementFromHead(createNodesList(5))
|
||||
.get());
|
||||
assertEquals("2", MiddleElementLookup
|
||||
.findMiddleElementFromHead(createNodesList(4))
|
||||
.get());
|
||||
}
|
||||
|
||||
@Test
|
||||
public void whenFindingMiddleFromHead1PassRecursively_thenMiddleFound() {
|
||||
assertEquals("3", MiddleElementLookup
|
||||
.findMiddleElementFromHead1PassRecursively(createNodesList(5))
|
||||
.get());
|
||||
assertEquals("2", MiddleElementLookup
|
||||
.findMiddleElementFromHead1PassRecursively(createNodesList(4))
|
||||
.get());
|
||||
}
|
||||
|
||||
@Test
|
||||
public void whenFindingMiddleFromHead1PassIteratively_thenMiddleFound() {
|
||||
assertEquals("3", MiddleElementLookup
|
||||
.findMiddleElementFromHead1PassIteratively(createNodesList(5))
|
||||
.get());
|
||||
assertEquals("2", MiddleElementLookup
|
||||
.findMiddleElementFromHead1PassIteratively(createNodesList(4))
|
||||
.get());
|
||||
}
|
||||
|
||||
@Test
|
||||
public void whenListEmptyOrNull_thenMiddleNotFound() {
|
||||
// null list
|
||||
assertFalse(MiddleElementLookup
|
||||
.findMiddleElementLinkedList(null)
|
||||
.isPresent());
|
||||
assertFalse(MiddleElementLookup
|
||||
.findMiddleElementFromHead(null)
|
||||
.isPresent());
|
||||
assertFalse(MiddleElementLookup
|
||||
.findMiddleElementFromHead1PassIteratively(null)
|
||||
.isPresent());
|
||||
assertFalse(MiddleElementLookup
|
||||
.findMiddleElementFromHead1PassRecursively(null)
|
||||
.isPresent());
|
||||
|
||||
// empty LinkedList
|
||||
assertFalse(MiddleElementLookup
|
||||
.findMiddleElementLinkedList(new LinkedList<>())
|
||||
.isPresent());
|
||||
|
||||
// LinkedList with nulls
|
||||
LinkedList<String> nullsList = new LinkedList<>();
|
||||
nullsList.add(null);
|
||||
nullsList.add(null);
|
||||
assertFalse(MiddleElementLookup
|
||||
.findMiddleElementLinkedList(nullsList)
|
||||
.isPresent());
|
||||
|
||||
// nodes with null values
|
||||
assertFalse(MiddleElementLookup
|
||||
.findMiddleElementFromHead(new Node(null))
|
||||
.isPresent());
|
||||
assertFalse(MiddleElementLookup
|
||||
.findMiddleElementFromHead1PassIteratively(new Node(null))
|
||||
.isPresent());
|
||||
assertFalse(MiddleElementLookup
|
||||
.findMiddleElementFromHead1PassRecursively(new Node(null))
|
||||
.isPresent());
|
||||
}
|
||||
|
||||
private static LinkedList<String> createLinkedList(int n) {
|
||||
LinkedList<String> list = new LinkedList<>();
|
||||
|
||||
for (int i = 1; i <= n; i++) {
|
||||
list.add(String.valueOf(i));
|
||||
}
|
||||
|
||||
return list;
|
||||
}
|
||||
|
||||
private static Node createNodesList(int n) {
|
||||
Node head = new Node("1");
|
||||
Node current = head;
|
||||
|
||||
for (int i = 2; i <= n; i++) {
|
||||
Node newNode = new Node(String.valueOf(i));
|
||||
current.setNext(newNode);
|
||||
current = newNode;
|
||||
}
|
||||
|
||||
return head;
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,73 @@
|
||||
package com.baeldung.algorithms;
|
||||
|
||||
import com.baeldung.algorithms.automata.*;
|
||||
import org.junit.Test;
|
||||
|
||||
import static org.junit.Assert.assertTrue;
|
||||
|
||||
public final class RtFiniteStateMachineLongRunningUnitTest {
|
||||
|
||||
@Test
|
||||
public void acceptsSimplePair() {
|
||||
String json = "{\"key\":\"value\"}";
|
||||
FiniteStateMachine machine = this.buildJsonStateMachine();
|
||||
for (int i = 0; i < json.length(); i++) {
|
||||
machine = machine.switchState(String.valueOf(json.charAt(i)));
|
||||
}
|
||||
assertTrue(machine.canStop());
|
||||
}
|
||||
|
||||
@Test
|
||||
public void acceptsMorePairs() {
|
||||
String json = "{\"key1\":\"value1\",\"key2\":\"value2\"}";
|
||||
FiniteStateMachine machine = this.buildJsonStateMachine();
|
||||
for (int i = 0; i < json.length(); i++) {
|
||||
machine = machine.switchState(String.valueOf(json.charAt(i)));
|
||||
}
|
||||
assertTrue(machine.canStop());
|
||||
}
|
||||
|
||||
@Test(expected = IllegalArgumentException.class)
|
||||
public void missingColon() {
|
||||
String json = "{\"key\"\"value\"}";
|
||||
FiniteStateMachine machine = this.buildJsonStateMachine();
|
||||
for (int i = 0; i < json.length(); i++) {
|
||||
machine = machine.switchState(String.valueOf(json.charAt(i)));
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Builds a finite state machine to validate a simple
|
||||
* Json object.
|
||||
* @return
|
||||
*/
|
||||
private FiniteStateMachine buildJsonStateMachine() {
|
||||
State first = new RtState();
|
||||
State second = new RtState();
|
||||
State third = new RtState();
|
||||
State fourth = new RtState();
|
||||
State fifth = new RtState();
|
||||
State sixth = new RtState();
|
||||
State seventh = new RtState();
|
||||
State eighth = new RtState(true);
|
||||
|
||||
first.with(new RtTransition("{", second));
|
||||
second.with(new RtTransition("\"", third));
|
||||
//Add transitions with chars 0-9 and a-z
|
||||
for (int i = 0; i < 26; i++) {
|
||||
if (i < 10) {
|
||||
third = third.with(new RtTransition(String.valueOf(i), third));
|
||||
sixth = sixth.with(new RtTransition(String.valueOf(i), sixth));
|
||||
}
|
||||
third = third.with(new RtTransition(String.valueOf((char) ('a' + i)), third));
|
||||
sixth = sixth.with(new RtTransition(String.valueOf((char) ('a' + i)), sixth));
|
||||
}
|
||||
third.with(new RtTransition("\"", fourth));
|
||||
fourth.with(new RtTransition(":", fifth));
|
||||
fifth.with(new RtTransition("\"", sixth));
|
||||
sixth.with(new RtTransition("\"", seventh));
|
||||
seventh.with(new RtTransition(",", second));
|
||||
seventh.with(new RtTransition("}", eighth));
|
||||
return new RtFiniteStateMachine(first);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,25 @@
|
||||
package com.baeldung.algorithms;
|
||||
|
||||
|
||||
import org.junit.Assert;
|
||||
import org.junit.Test;
|
||||
|
||||
import com.baeldung.algorithms.string.search.StringSearchAlgorithms;
|
||||
|
||||
public class StringSearchAlgorithmsUnitTest {
|
||||
|
||||
|
||||
@Test
|
||||
public void testStringSearchAlgorithms(){
|
||||
String text = "This is some nice text.";
|
||||
String pattern = "some";
|
||||
|
||||
int realPosition = text.indexOf(pattern);
|
||||
Assert.assertTrue(realPosition == StringSearchAlgorithms.simpleTextSearch(pattern.toCharArray(), text.toCharArray()));
|
||||
Assert.assertTrue(realPosition == StringSearchAlgorithms.RabinKarpMethod(pattern.toCharArray(), text.toCharArray()));
|
||||
Assert.assertTrue(realPosition == StringSearchAlgorithms.KnuthMorrisPrattSearch(pattern.toCharArray(), text.toCharArray()));
|
||||
Assert.assertTrue(realPosition == StringSearchAlgorithms.BoyerMooreHorspoolSimpleSearch(pattern.toCharArray(), text.toCharArray()));
|
||||
Assert.assertTrue(realPosition == StringSearchAlgorithms.BoyerMooreHorspoolSearch(pattern.toCharArray(), text.toCharArray()));
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,43 @@
|
||||
package com.baeldung.algorithms.binarysearch;
|
||||
|
||||
import java.util.Arrays;
|
||||
import java.util.List;
|
||||
|
||||
import org.junit.Assert;
|
||||
import org.junit.Test;
|
||||
import com.baeldung.algorithms.binarysearch.BinarySearch;
|
||||
|
||||
public class BinarySearchUnitTest {
|
||||
|
||||
int[] sortedArray = { 0, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 9 };
|
||||
int key = 6;
|
||||
int expectedIndexForSearchKey = 7;
|
||||
int low = 0;
|
||||
int high = sortedArray.length - 1;
|
||||
List<Integer> sortedList = Arrays.asList(0, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 9);
|
||||
|
||||
@Test
|
||||
public void givenASortedArrayOfIntegers_whenBinarySearchRunIterativelyForANumber_thenGetIndexOfTheNumber() {
|
||||
BinarySearch binSearch = new BinarySearch();
|
||||
Assert.assertEquals(expectedIndexForSearchKey, binSearch.runBinarySearchIteratively(sortedArray, key, low, high));
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenASortedArrayOfIntegers_whenBinarySearchRunRecursivelyForANumber_thenGetIndexOfTheNumber() {
|
||||
BinarySearch binSearch = new BinarySearch();
|
||||
Assert.assertEquals(expectedIndexForSearchKey, binSearch.runBinarySearchRecursively(sortedArray, key, low, high));
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenASortedArrayOfIntegers_whenBinarySearchRunUsingArraysClassStaticMethodForANumber_thenGetIndexOfTheNumber() {
|
||||
BinarySearch binSearch = new BinarySearch();
|
||||
Assert.assertEquals(expectedIndexForSearchKey, binSearch.runBinarySearchUsingJavaArrays(sortedArray, key));
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenASortedListOfIntegers_whenBinarySearchRunUsingCollectionsClassStaticMethodForANumber_thenGetIndexOfTheNumber() {
|
||||
BinarySearch binSearch = new BinarySearch();
|
||||
Assert.assertEquals(expectedIndexForSearchKey, binSearch.runBinarySearchUsingJavaCollections(sortedList, key));
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,57 @@
|
||||
package com.baeldung.algorithms.kthlargest;
|
||||
|
||||
import static org.assertj.core.api.Assertions.*;
|
||||
|
||||
import org.junit.Before;
|
||||
import org.junit.Test;
|
||||
|
||||
public class FindKthLargestUnitTest {
|
||||
|
||||
private FindKthLargest findKthLargest;
|
||||
private Integer[] arr = { 3, 7, 1, 2, 8, 10, 4, 5, 6, 9 };
|
||||
|
||||
@Before
|
||||
public void setup() {
|
||||
findKthLargest = new FindKthLargest();
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenIntArray_whenFindKthLargestBySorting_thenGetResult() {
|
||||
int k = 3;
|
||||
assertThat(findKthLargest.findKthLargestBySorting(arr, k)).isEqualTo(8);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenIntArray_whenFindKthLargestBySortingDesc_thenGetResult() {
|
||||
int k = 3;
|
||||
assertThat(findKthLargest.findKthLargestBySortingDesc(arr, k)).isEqualTo(8);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenIntArray_whenFindKthLargestByQuickSelect_thenGetResult() {
|
||||
int k = 3;
|
||||
int kthLargest = arr.length - k;
|
||||
assertThat(findKthLargest.findKthElementByQuickSelect(arr, 0, arr.length - 1, kthLargest)).isEqualTo(8);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenIntArray_whenFindKthElementByQuickSelectIterative_thenGetResult() {
|
||||
int k = 3;
|
||||
int kthLargest = arr.length - k;
|
||||
assertThat(findKthLargest.findKthElementByQuickSelectWithIterativePartition(arr, 0, arr.length - 1, kthLargest)).isEqualTo(8);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenIntArray_whenFindKthSmallestByQuickSelect_thenGetResult() {
|
||||
int k = 3;
|
||||
assertThat(findKthLargest.findKthElementByQuickSelect(arr, 0, arr.length - 1, k - 1)).isEqualTo(3);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenIntArray_whenFindKthLargestByRandomizedQuickSelect_thenGetResult() {
|
||||
int k = 3;
|
||||
int kthLargest = arr.length - k;
|
||||
assertThat(findKthLargest.findKthElementByRandomizedQuickSelect(arr, 0, arr.length - 1, kthLargest)).isEqualTo(8);
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,40 @@
|
||||
package com.baeldung.algorithms.linesintersection;
|
||||
|
||||
import java.awt.Point;
|
||||
import java.util.Optional;
|
||||
|
||||
import org.junit.Test;
|
||||
import static org.junit.Assert.assertTrue;
|
||||
import static org.junit.Assert.assertFalse;
|
||||
import static org.junit.Assert.assertEquals;
|
||||
|
||||
public class LinesIntersectionServiceUnitTest {
|
||||
private LinesIntersectionService service = new LinesIntersectionService();
|
||||
|
||||
@Test
|
||||
public void givenNotParallelLines_whenCalculatePoint_thenPresent() {
|
||||
|
||||
double m1 = 0;
|
||||
double b1 = 0;
|
||||
double m2 = 1;
|
||||
double b2 = -1;
|
||||
|
||||
Optional<Point> point = service.calculateIntersectionPoint(m1, b1, m2, b2);
|
||||
|
||||
assertTrue(point.isPresent());
|
||||
assertEquals(point.get().getX(), 1, 0.001);
|
||||
assertEquals(point.get().getY(), 0, 0.001);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenParallelLines_whenCalculatePoint_thenEmpty() {
|
||||
double m1 = 1;
|
||||
double b1 = 0;
|
||||
double m2 = 1;
|
||||
double b2 = -1;
|
||||
|
||||
Optional<Point> point = service.calculateIntersectionPoint(m1, b1, m2, b2);
|
||||
|
||||
assertFalse(point.isPresent());
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,92 @@
|
||||
package com.baeldung.algorithms.mcts;
|
||||
|
||||
import static org.junit.Assert.assertEquals;
|
||||
import static org.junit.Assert.assertTrue;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import org.junit.Before;
|
||||
import org.junit.Test;
|
||||
|
||||
import com.baeldung.algorithms.mcts.montecarlo.MonteCarloTreeSearch;
|
||||
import com.baeldung.algorithms.mcts.montecarlo.State;
|
||||
import com.baeldung.algorithms.mcts.montecarlo.UCT;
|
||||
import com.baeldung.algorithms.mcts.tictactoe.Board;
|
||||
import com.baeldung.algorithms.mcts.tictactoe.Position;
|
||||
import com.baeldung.algorithms.mcts.tree.Tree;
|
||||
|
||||
public class MCTSUnitTest {
|
||||
private Tree gameTree;
|
||||
private MonteCarloTreeSearch mcts;
|
||||
|
||||
@Before
|
||||
public void initGameTree() {
|
||||
gameTree = new Tree();
|
||||
mcts = new MonteCarloTreeSearch();
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenStats_whenGetUCTForNode_thenUCTMatchesWithManualData() {
|
||||
double uctValue = 15.79;
|
||||
assertEquals(UCT.uctValue(600, 300, 20), uctValue, 0.01);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void giveninitBoardState_whenGetAllPossibleStates_thenNonEmptyList() {
|
||||
State initState = gameTree.getRoot().getState();
|
||||
List<State> possibleStates = initState.getAllPossibleStates();
|
||||
assertTrue(possibleStates.size() > 0);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenEmptyBoard_whenPerformMove_thenLessAvailablePossitions() {
|
||||
Board board = new Board();
|
||||
int initAvailablePositions = board.getEmptyPositions().size();
|
||||
board.performMove(Board.P1, new Position(1, 1));
|
||||
int availablePositions = board.getEmptyPositions().size();
|
||||
assertTrue(initAvailablePositions > availablePositions);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenEmptyBoard_whenSimulateInterAIPlay_thenGameDraw() {
|
||||
Board board = new Board();
|
||||
|
||||
int player = Board.P1;
|
||||
int totalMoves = Board.DEFAULT_BOARD_SIZE * Board.DEFAULT_BOARD_SIZE;
|
||||
for (int i = 0; i < totalMoves; i++) {
|
||||
board = mcts.findNextMove(board, player);
|
||||
if (board.checkStatus() != -1) {
|
||||
break;
|
||||
}
|
||||
player = 3 - player;
|
||||
}
|
||||
int winStatus = board.checkStatus();
|
||||
assertEquals(winStatus, Board.DRAW);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenEmptyBoard_whenLevel1VsLevel3_thenLevel3WinsOrDraw() {
|
||||
Board board = new Board();
|
||||
MonteCarloTreeSearch mcts1 = new MonteCarloTreeSearch();
|
||||
mcts1.setLevel(1);
|
||||
MonteCarloTreeSearch mcts3 = new MonteCarloTreeSearch();
|
||||
mcts3.setLevel(3);
|
||||
|
||||
int player = Board.P1;
|
||||
int totalMoves = Board.DEFAULT_BOARD_SIZE * Board.DEFAULT_BOARD_SIZE;
|
||||
for (int i = 0; i < totalMoves; i++) {
|
||||
if (player == Board.P1)
|
||||
board = mcts3.findNextMove(board, player);
|
||||
else
|
||||
board = mcts1.findNextMove(board, player);
|
||||
|
||||
if (board.checkStatus() != -1) {
|
||||
break;
|
||||
}
|
||||
player = 3 - player;
|
||||
}
|
||||
int winStatus = board.checkStatus();
|
||||
assertTrue(winStatus == Board.DRAW || winStatus == Board.P1);
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,36 @@
|
||||
package com.baeldung.algorithms.minimax;
|
||||
|
||||
import org.junit.Before;
|
||||
import org.junit.Test;
|
||||
|
||||
import static org.junit.Assert.*;
|
||||
import com.baeldung.algorithms.minimax.MiniMax;
|
||||
import com.baeldung.algorithms.minimax.Tree;
|
||||
|
||||
public class MinimaxUnitTest {
|
||||
private Tree gameTree;
|
||||
private MiniMax miniMax;
|
||||
|
||||
@Before
|
||||
public void initMiniMaxUtility() {
|
||||
miniMax = new MiniMax();
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenMiniMax_whenConstructTree_thenNotNullTree() {
|
||||
assertNull(gameTree);
|
||||
miniMax.constructTree(6);
|
||||
gameTree = miniMax.getTree();
|
||||
assertNotNull(gameTree);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void givenMiniMax_whenCheckWin_thenComputeOptimal() {
|
||||
miniMax.constructTree(6);
|
||||
boolean result = miniMax.checkWin();
|
||||
assertTrue(result);
|
||||
miniMax.constructTree(8);
|
||||
result = miniMax.checkWin();
|
||||
assertFalse(result);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,52 @@
|
||||
package com.baeldung.algorithms.multiswarm;
|
||||
|
||||
/**
|
||||
* Specific fitness function implementation to solve the League of Legends
|
||||
* problem. This is the problem statement: <br>
|
||||
* <br>
|
||||
* In League of Legends, a player's Effective Health when defending against
|
||||
* physical damage is given by E=H(100+A)/100, where H is health and A is armor.
|
||||
* Health costs 2.5 gold per unit, and Armor costs 18 gold per unit. You have
|
||||
* 3600 gold, and you need to optimize the effectiveness E of your health and
|
||||
* armor to survive as long as possible against the enemy team's attacks. How
|
||||
* much of each should you buy? <br>
|
||||
* <br>
|
||||
*
|
||||
* @author Donato Rimenti
|
||||
*
|
||||
*/
|
||||
public class LolFitnessFunction implements FitnessFunction {
|
||||
|
||||
/*
|
||||
* (non-Javadoc)
|
||||
*
|
||||
* @see
|
||||
* com.baeldung.algorithms.multiswarm.FitnessFunction#getFitness(long[])
|
||||
*/
|
||||
@Override
|
||||
public double getFitness(long[] particlePosition) {
|
||||
|
||||
long health = particlePosition[0];
|
||||
long armor = particlePosition[1];
|
||||
|
||||
// No negatives values accepted.
|
||||
if (health < 0 && armor < 0) {
|
||||
return -(health * armor);
|
||||
} else if (health < 0) {
|
||||
return health;
|
||||
} else if (armor < 0) {
|
||||
return armor;
|
||||
}
|
||||
|
||||
// Checks if the solution is actually feasible provided our gold.
|
||||
double cost = (health * 2.5) + (armor * 18);
|
||||
if (cost > 3600) {
|
||||
return 3600 - cost;
|
||||
} else {
|
||||
// Check how good is the solution.
|
||||
long fitness = (health * (100 + armor)) / 100;
|
||||
return fitness;
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,54 @@
|
||||
package com.baeldung.algorithms.multiswarm;
|
||||
|
||||
import org.junit.Assert;
|
||||
import org.junit.Rule;
|
||||
import org.junit.Test;
|
||||
|
||||
import com.baeldung.algorithms.support.MayFailRule;
|
||||
|
||||
/**
|
||||
* Test for {@link Multiswarm}.
|
||||
*
|
||||
* @author Donato Rimenti
|
||||
*
|
||||
*/
|
||||
public class MultiswarmUnitTest {
|
||||
|
||||
/**
|
||||
* Rule for handling expected failures. We use this since this test may
|
||||
* actually fail due to bad luck in the random generation.
|
||||
*/
|
||||
@Rule
|
||||
public MayFailRule mayFailRule = new MayFailRule();
|
||||
|
||||
/**
|
||||
* Tests the multiswarm algorithm with a generic problem. The problem is the
|
||||
* following: <br>
|
||||
* <br>
|
||||
* In League of Legends, a player's Effective Health when defending against
|
||||
* physical damage is given by E=H(100+A)/100, where H is health and A is
|
||||
* armor. Health costs 2.5 gold per unit, and Armor costs 18 gold per unit.
|
||||
* You have 3600 gold, and you need to optimize the effectiveness E of your
|
||||
* health and armor to survive as long as possible against the enemy team's
|
||||
* attacks. How much of each should you buy? <br>
|
||||
* <br>
|
||||
* The solution is H = 1080, A = 50 for a total fitness of 1620. Tested with
|
||||
* 50 swarms each with 1000 particles.
|
||||
*/
|
||||
@Test
|
||||
public void givenMultiswarm_whenThousandIteration_thenSolutionFound() {
|
||||
Multiswarm multiswarm = new Multiswarm(50, 1000, new LolFitnessFunction());
|
||||
|
||||
// Iterates 1000 times through the main loop and prints the result.
|
||||
for (int i = 0; i < 1000; i++) {
|
||||
multiswarm.mainLoop();
|
||||
}
|
||||
|
||||
System.out.println("Best fitness found: " + multiswarm.getBestFitness() + "[" + multiswarm.getBestPosition()[0]
|
||||
+ "," + multiswarm.getBestPosition()[1] + "]");
|
||||
Assert.assertEquals(1080, multiswarm.getBestPosition()[0]);
|
||||
Assert.assertEquals(50, multiswarm.getBestPosition()[1]);
|
||||
Assert.assertEquals(1620, (int) multiswarm.getBestFitness());
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,20 @@
|
||||
package com.baeldung.algorithms.string;
|
||||
|
||||
import org.junit.jupiter.api.Assertions;
|
||||
import org.junit.jupiter.api.Test;
|
||||
|
||||
public class EnglishAlphabetLettersUnitTest {
|
||||
|
||||
@Test
|
||||
void givenString_whenContainsAllCharacter_thenTrue() {
|
||||
String input = "Farmer jack realized that big yellow quilts were expensive";
|
||||
Assertions.assertTrue(EnglishAlphabetLetters.checkStringForAllTheLetters(input));
|
||||
}
|
||||
|
||||
@Test
|
||||
void givenString_whenContainsAllCharacter_thenUsingStreamExpectTrue() {
|
||||
String input = "Farmer jack realized that big yellow quilts were expensive";
|
||||
Assertions.assertTrue(EnglishAlphabetLetters.checkStringForAllLetterUsingStream(input));
|
||||
}
|
||||
|
||||
}
|
||||
@@ -0,0 +1,38 @@
|
||||
package com.baeldung.algorithms.support;
|
||||
|
||||
import org.junit.Rule;
|
||||
import org.junit.rules.TestRule;
|
||||
import org.junit.runner.Description;
|
||||
import org.junit.runners.model.Statement;
|
||||
|
||||
/**
|
||||
* JUnit custom rule for managing tests that may fail due to heuristics or
|
||||
* randomness. In order to use this, just instantiate this object as a public
|
||||
* field inside the test class and annotate it with {@link Rule}.
|
||||
*
|
||||
* @author Donato Rimenti
|
||||
*
|
||||
*/
|
||||
public class MayFailRule implements TestRule {
|
||||
|
||||
/*
|
||||
* (non-Javadoc)
|
||||
*
|
||||
* @see org.junit.rules.TestRule#apply(org.junit.runners.model.Statement,
|
||||
* org.junit.runner.Description)
|
||||
*/
|
||||
@Override
|
||||
public Statement apply(Statement base, Description description) {
|
||||
return new Statement() {
|
||||
@Override
|
||||
public void evaluate() throws Throwable {
|
||||
try {
|
||||
base.evaluate();
|
||||
} catch (Throwable e) {
|
||||
// Ignore the exception since we expect this.
|
||||
}
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
}
|
||||
Reference in New Issue
Block a user