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Add tests for AStar.java, enhance documentation (#5603)

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This commit is contained in:
Hardik Pawar
2024-10-07 21:55:48 +05:30
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parent d422bf5983
commit 62144f61af
3 changed files with 92 additions and 99 deletions
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1
DIRECTORY.md
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@ -694,6 +694,7 @@
* dynamicarray
* [DynamicArrayTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/datastructures/dynamicarray/DynamicArrayTest.java)
* graphs
* [AStarTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/datastructures/graphs/AStarTest.java)
* [BipartiteGraphDFSTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/datastructures/graphs/BipartiteGraphDFSTest.java)
* [BoruvkaAlgorithmTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/datastructures/graphs/BoruvkaAlgorithmTest.java)
* [DijkstraAlgorithmTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/datastructures/graphs/DijkstraAlgorithmTest.java)

144
src/main/java/com/thealgorithms/datastructures/graphs/AStar.java
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@ -1,25 +1,26 @@
/*
Time Complexity = O(E), where E is equal to the number of edges
*/
package com.thealgorithms.datastructures.graphs;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Comparator;
import java.util.List;
import java.util.PriorityQueue;
/**
* AStar class implements the A* pathfinding algorithm to find the shortest path in a graph.
* The graph is represented using an adjacency list, and the algorithm uses a heuristic to estimate
* the cost to reach the destination node.
* Time Complexity = O(E), where E is equal to the number of edges
*/
public final class AStar {
private AStar() {
}
private static class Graph {
// Graph's structure can be changed only applying changes to this class.
/**
* Represents a graph using an adjacency list.
*/
static class Graph {
private ArrayList<ArrayList<Edge>> graph;
// Initialise ArrayLists in Constructor
Graph(int size) {
this.graph = new ArrayList<>();
for (int i = 0; i < size; i++) {
@ -31,15 +32,17 @@ public final class AStar {
return this.graph.get(from);
}
// Graph is bidirectional, for just one direction remove second instruction of this method.
// Add a bidirectional edge to the graph
private void addEdge(Edge edge) {
this.graph.get(edge.getFrom()).add(new Edge(edge.getFrom(), edge.getTo(), edge.getWeight()));
this.graph.get(edge.getTo()).add(new Edge(edge.getTo(), edge.getFrom(), edge.getWeight()));
}
}
/**
* Represents an edge in the graph with a start node, end node, and weight.
*/
private static class Edge {
private int from;
private int to;
private int weight;
@ -63,12 +66,13 @@ public final class AStar {
}
}
// class to iterate during the algorithm execution, and also used to return the solution.
private static class PathAndDistance {
private int distance; // distance advanced so far.
private ArrayList<Integer> path; // list of visited nodes in this path.
private int estimated; // heuristic value associated to the last node od the path (current node).
/**
* Contains information about the path and its total distance.
*/
static class PathAndDistance {
private int distance; // total distance from the start node
private ArrayList<Integer> path; // list of nodes in the path
private int estimated; // heuristic estimate for reaching the destination
PathAndDistance(int distance, ArrayList<Integer> path, int estimated) {
this.distance = distance;
@ -87,112 +91,54 @@ public final class AStar {
public int getEstimated() {
return estimated;
}
private void printSolution() {
if (this.path != null) {
System.out.println("Optimal path: " + this.path + ", distance: " + this.distance);
} else {
System.out.println("There is no path available to connect the points");
}
}
}
private static void initializeGraph(Graph graph, ArrayList<Integer> data) {
// Initializes the graph with edges defined in the input data
static void initializeGraph(Graph graph, ArrayList<Integer> data) {
for (int i = 0; i < data.size(); i += 4) {
graph.addEdge(new Edge(data.get(i), data.get(i + 1), data.get(i + 2)));
}
/*
.x. node
(y) cost
- or | or / bidirectional connection
( 98)- .7. -(86)- .4.
|
( 85)- .17. -(142)- .18. -(92)- .8. -(87)- .11.
|
. 1. -------------------- (160)
| \ |
(211) \ .6.
| \ |
. 5. (101)-.13. -(138) (115)
| | | /
( 99) ( 97) | /
| | | /
.12. -(151)- .15. -(80)- .14. | /
| | | | /
( 71) (140) (146)- .2. -(120)
| | |
.19. -( 75)- . 0. .10. -(75)- .3.
| |
(118) ( 70)
| |
.16. -(111)- .9.
*/
}
public static void main(String[] args) {
// heuristic function optimistic values
int[] heuristic = {
366,
0,
160,
242,
161,
178,
77,
151,
226,
244,
241,
234,
380,
98,
193,
253,
329,
80,
199,
374,
};
Graph graph = new Graph(20);
ArrayList<Integer> graphData = new ArrayList<>(Arrays.asList(0, 19, 75, null, 0, 15, 140, null, 0, 16, 118, null, 19, 12, 71, null, 12, 15, 151, null, 16, 9, 111, null, 9, 10, 70, null, 10, 3, 75, null, 3, 2, 120, null, 2, 14, 146, null, 2, 13, 138, null, 2, 6, 115, null, 15, 14, 80, null,
15, 5, 99, null, 14, 13, 97, null, 5, 1, 211, null, 13, 1, 101, null, 6, 1, 160, null, 1, 17, 85, null, 17, 7, 98, null, 7, 4, 86, null, 17, 18, 142, null, 18, 8, 92, null, 8, 11, 87));
initializeGraph(graph, graphData);
PathAndDistance solution = aStar(3, 1, graph, heuristic);
solution.printSolution();
}
/**
* Implements the A* pathfinding algorithm to find the shortest path from a start node to a destination node.
*
* @param from the starting node
* @param to the destination node
* @param graph the graph representation of the problem
* @param heuristic the heuristic estimates for each node
* @return a PathAndDistance object containing the shortest path and its distance
*/
public static PathAndDistance aStar(int from, int to, Graph graph, int[] heuristic) {
// nodes are prioritised by the less value of the current distance of their paths, and the
// estimated value
// given by the heuristic function to reach the destination point from the current point.
// PriorityQueue to explore nodes based on their distance and estimated cost to reach the destination
PriorityQueue<PathAndDistance> queue = new PriorityQueue<>(Comparator.comparingInt(a -> (a.getDistance() + a.getEstimated())));
// dummy data to start the algorithm from the beginning point
queue.add(new PathAndDistance(0, new ArrayList<>(List.of(from)), 0));
// Start with the initial node
queue.add(new PathAndDistance(0, new ArrayList<>(List.of(from)), heuristic[from]));
boolean solutionFound = false;
PathAndDistance currentData = new PathAndDistance(-1, null, -1);
while (!queue.isEmpty() && !solutionFound) {
currentData = queue.poll(); // first in the queue, best node so keep exploring.
int currentPosition = currentData.getPath().get(currentData.getPath().size() - 1); // current node.
currentData = queue.poll(); // get the best node from the queue
int currentPosition = currentData.getPath().get(currentData.getPath().size() - 1); // current node
// Check if the destination has been reached
if (currentPosition == to) {
solutionFound = true;
} else {
for (Edge edge : graph.getNeighbours(currentPosition)) {
if (!currentData.getPath().contains(edge.getTo())) { // Avoid Cycles
// Avoid cycles by checking if the next node is already in the path
if (!currentData.getPath().contains(edge.getTo())) {
ArrayList<Integer> updatedPath = new ArrayList<>(currentData.getPath());
updatedPath.add(edge.getTo()); // Add the new node to the path, update the distance,
// and the heuristic function value associated to that path.
updatedPath.add(edge.getTo());
// Update the distance and heuristic for the new path
queue.add(new PathAndDistance(currentData.getDistance() + edge.getWeight(), updatedPath, heuristic[edge.getTo()]));
}
}
}
}
return (solutionFound) ? currentData : new PathAndDistance(-1, null, -1);
// Out of while loop, if there is a solution, the current Data stores the optimal path, and
// its distance
}
}

46
src/test/java/com/thealgorithms/datastructures/graphs/AStarTest.java Normal file
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@ -0,0 +1,46 @@
package com.thealgorithms.datastructures.graphs;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertNull;
import java.util.ArrayList;
import java.util.Arrays;
import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Test;
public class AStarTest {
private AStar.Graph graph;
private int[] heuristic;
@BeforeEach
public void setUp() {
// Initialize graph and heuristic values for testing
graph = new AStar.Graph(5);
ArrayList<Integer> graphData = new ArrayList<>(Arrays.asList(0, 1, 1, null, 0, 2, 2, null, 1, 3, 1, null, 2, 3, 1, null, 3, 4, 1, null));
AStar.initializeGraph(graph, graphData);
heuristic = new int[] {5, 4, 3, 2, 0}; // Heuristic values for each node
}
@Test
public void testAStarFindsPath() {
AStar.PathAndDistance result = AStar.aStar(0, 4, graph, heuristic);
assertEquals(3, result.getDistance(), "Expected distance from 0 to 4 is 3");
assertEquals(Arrays.asList(0, 1, 3, 4), result.getPath(), "Expected path from 0 to 4");
}
@Test
public void testAStarPathNotFound() {
AStar.PathAndDistance result = AStar.aStar(0, 5, graph, heuristic); // Node 5 does not exist
assertEquals(-1, result.getDistance(), "Expected distance when path not found is -1");
assertNull(result.getPath(), "Expected path should be null when no path exists");
}
@Test
public void testAStarSameNode() {
AStar.PathAndDistance result = AStar.aStar(0, 0, graph, heuristic);
assertEquals(0, result.getDistance(), "Expected distance from 0 to 0 is 0");
assertEquals(Arrays.asList(0), result.getPath(), "Expected path should only contain the start node");
}
}