public void Test_IsEmpty_FilledQ()
{
PriorityQueue <double> q = null;
q = new MinPriorityQueue <double>();
q.Enqueue(1);
q.Enqueue(2);
Assert.IsFalse(q.IsEmpty);
}
public void Test_Count()
{
PriorityQueue <double> q = null;
q = new MinPriorityQueue <double>();
q.Enqueue(1);
q.Enqueue(2);
Assert.AreEqual(2, q.Count);
}
public void Test_Contains_Not()
{
PriorityQueue <double> q = null;
q = new MinPriorityQueue <double>();
q.Enqueue(3);
q.Enqueue(2);
q.Enqueue(1);
Assert.IsFalse(q.Contains(4));
}
public void Test_Enqueue()
{
PriorityQueue <double> q = null;
q = new MinPriorityQueue <double>();
q.Enqueue(3);
q.Enqueue(2);
q.Enqueue(1);
Assert.AreEqual(1, q.Peek());
}
public void Test_Capacity_AutoResize()
{
PriorityQueue <double> q = null;
q = new MinPriorityQueue <double>(3);
q.Enqueue(1);
q.Enqueue(2);
q.Enqueue(3);
q.Enqueue(4);
Assert.AreEqual(6, q.Capacity);
}
public IEnumerable <Node> GetPath(Node start, Node goal)
{
var cost = new Dictionary <Node, int>();
var parents = new Dictionary <Node, Node>();
var visited = new HashSet <Node>();
var queue = new MinPriorityQueue <Node>();
cost[start] = 0;
parents[start] = null;
queue.Enqueue(start);
bool foundPath = false;
while (queue.Count > 0)
{
var current = queue.Dequeue();
visited.Add(current);
if (current.Equals(goal))
{
foundPath = true;
break;
}
var neighbours = this.GetNeighbours(current);
foreach (var neighbour in neighbours)
{
if (visited.Contains(neighbour) || this.IsWall(neighbour))
{
continue;
}
var newCost = cost[current] + 1;
if (!cost.ContainsKey(neighbour) || newCost < cost[neighbour])
{
cost[neighbour] = newCost;
neighbour.F = newCost + this.GetH(neighbour, goal);
queue.Enqueue(neighbour);
parents[neighbour] = current;
}
}
}
if (!foundPath)
{
throw new InvalidOperationException("No path found.");
}
return(this.GetPath(parents, goal));
}
public void Test_PriorityUpgrade()
{
PriorityQueue <double> q = null;
q = new MinPriorityQueue <double>();
q.Enqueue(30);
q.Enqueue(20);
q.Enqueue(10);
q.Remove(20);
q.Enqueue(5);
Assert.AreEqual(5, q.Peek());
}
public void PriorityQueue_Test()
{
var queue = new MinPriorityQueue <int>();
queue.Enqueue(10);
queue.Enqueue(9);
queue.Enqueue(1);
queue.Enqueue(21);
Assert.AreEqual(queue.Dequeue(), 1);
Assert.AreEqual(queue.Dequeue(), 9);
Assert.AreEqual(queue.Dequeue(), 10);
Assert.AreEqual(queue.Dequeue(), 21);
}
/************************************************************************************************************/
/// <summary>
/// The Dijkstra's algorithm.
/// </summary>
private void _dijkstra(TGraph graph, TVertex source)
{
var minPQ = new MinPriorityQueue <TVertex, decimal>((uint)_verticesCount);
var srcIndex = _nodesToIndices[source];
_srcIndex = srcIndex;
_distances[srcIndex] = 0;
minPQ.Enqueue(source, _distances[srcIndex]);
// Main loop
while (!minPQ.IsEmpty)
{
var current = minPQ.DequeueMin(); // get vertex with min weight
var currentIndex = _nodesToIndices[current]; // get its index
var edges = graph.OutgoingEdges(current) as IEnumerable <WeightedEdge <TVertex> >; // get its outgoing weighted edges
foreach (var edge in edges)
{
var adjacentIndex = _nodesToIndices[edge.Destination];
// calculate a new possible weighted path if the edge weight is less than infinity
var delta = Infinity;
if (edge.Weight < Infinity && _distances[currentIndex] + edge.Weight < Infinity) // Handles overflow
{
delta = _distances[currentIndex] + edge.Weight;
}
// Relax the edge
// if check is true, a shorter path is found from current to adjacent
if (delta < _distances[adjacentIndex])
{
_edgeTo[adjacentIndex] = edge;
_distances[adjacentIndex] = delta;
_predecessors[adjacentIndex] = currentIndex;
// decrease priority with a new distance if it exists; otherwise enqueque it
if (minPQ.Contains(edge.Destination))
{
minPQ.UpdatePriority(edge.Destination, delta);
}
else
{
minPQ.Enqueue(edge.Destination, delta);
}
}
} //end-foreach
} //end-while
}
public void Peek_Should_Return_The_Min_Value_Without_Removing()
{
var pq = new MinPriorityQueue <int>();
pq.Enqueue(5);
pq.Enqueue(3);
pq.Enqueue(8);
pq.Enqueue(1);
var result = pq.Peek();
result.Should().Be(1);
pq.Count.Should().Be(4);
}
public void TryDequeue_Should_Return_True_And_Outs_The_Min_Value_When_Queue_Is_Not_Empty()
{
var pq = new MinPriorityQueue <int>();
pq.Enqueue(5);
pq.Enqueue(3);
pq.Enqueue(8);
pq.Enqueue(1);
var result = pq.TryDequeue(out var value);
result.Should().BeTrue();
value.Should().Be(1);
pq.Count.Should().Be(3);
}
/// <summary>
/// Nearest neighbor search method to find the single nearest neighbor at a given point.
/// Translated from https://github.com/gvd/kdtree/blob/master/kdtree.h
/// </summary>
/// <param name="query">The nearest neighbor search query point.</param>
/// <returns>The closest node to the parameter query is returned.</returns>
//public KDNode NNSearch(Point query)
//{
// MinPriorityQueue<Tuple<double, KDNode>> pq = new MinPriorityQueue<Tuple<double, KDNode>>();
// //Tuple<double, KDNode> best = new Tuple<double, KDNode>(1.79769e+308, root);
// pq.Enqueue(new Tuple<double, KDNode>(0.0, root));
// do
// {
// var current = pq.Dequeue();
// //if (current.Item1 >= best.Item1)
// //{
// // if (EuclideanDistance(query, current.Item2.Data) > EuclideanDistance(query, best.Item2.Data))
// // return best.Item2;
// // else
// // return current.Item2;
// //}
// List<KDNode> a = new List<KDNode>
// {
// };
// var currentNode = current.Item2;
// //double d = EuclideanDistance(query, currentNode.Data);
// //double dx = Subtract(query, currentNode.Data, currentNode.Depth);
// if ()
// {
// best = new Tuple<double, KDNode>(d, currentNode);
// }
// KDNode near, far;
// near = currentNode.Left;
// else
// near = currentNode.Right;
// far = currentNode.Right;
// else
// far = currentNode.Left;
// if (near != null)
// pq.Enqueue(new Tuple<double, KDNode>(0, near));
// if (far != null)
// pq.Enqueue(new Tuple<double, KDNode>(0, far));
// } while (pq.Count() != 0);
// return best.Item2;
//}
public List <KDNode> LocSearch(Point query)
{
MinPriorityQueue <Tuple <double, KDNode> > pq = new MinPriorityQueue <Tuple <double, KDNode> >();
Point p = new Point(0, 0);
List <KDNode> a = new List <KDNode>
{
};
pq.Enqueue(new Tuple <double, KDNode>(0.0, root));
do
{
var current = pq.Dequeue();
// current.Item2.Data;
var currentNode = current.Item2;
if (query.x < currentNode.Data.x && currentNode.Data.x < query.x && query.y < currentNode.Data.y)
{
a.Add(currentNode);
}
double d = EuclideanDistance(query, currentNode.Data);
double dx = Subtract(query, currentNode.Data, currentNode.Depth);
KDNode near;
if (dx <= 0)
{
near = currentNode.Left;
}
else
{
near = currentNode.Right;
}
//if (dx <= 0)
// far = currentNode.Right;
//else
// far = currentNode.Left;
if (near != null)
{
pq.Enqueue(new Tuple <double, KDNode>(0, near));
}
} while (pq.Count() != 0);
return(a);
}
public void MinPriorityQueueDoesNotInsertItemToHeadIfItemIsHigherPriorityThanHead()
{
var priorityQueue = new MinPriorityQueue <string, int>(50);
List <Tuple <string, int> > items = new List <Tuple <string, int> >
{
new Tuple <string, int>("A_50", 50),
new Tuple <string, int>("A_41", 41),
new Tuple <string, int>("A_38", 38),
new Tuple <string, int>("A_37", 37),
new Tuple <string, int>("A_23", 23),
new Tuple <string, int>("A_11", 11),
new Tuple <string, int>("A_5", 5),
new Tuple <string, int>("A_3", 3),
}.Randomize()
.ToList();
priorityQueue.EnqueueRange(items);
string originalHead = priorityQueue.Peek();
priorityQueue.Enqueue("A_4", 4);
string newHead = priorityQueue.Peek();
Assert.AreEqual("A_3", originalHead);
Assert.AreEqual("A_3", newHead);
}
public void MinPriorityQueue_FullTest_Successful()
{
var source = new List <int>();
var sourceCount = Faker.RandomNumber.Next(20, 100);
for (int i = 0; i < sourceCount; i++)
{
source.Add(Faker.RandomNumber.Next());
}
var additionalDataCount = Faker.RandomNumber.Next(10, 50);
// Act 1. Build priority queue with some initial data.
var queue = new MinPriorityQueue <int>(source);
// Act 2. Add some additional data using Enqueue
for (int i = 0; i < additionalDataCount; i++)
{
queue.Enqueue(Faker.RandomNumber.Next());
}
// Act 3 & Assert - Check results from the queue
var prev = -1; // Set a negative number as previous; all data in the queue is assumed to be positive.
while (!queue.IsEmpty())
{
var curr = queue.Dequeue();
Assert.IsTrue(curr >= prev);
prev = curr;
}
}
public void Test_Remove()
{
PriorityQueue <double> q = null;
double[] items = { 5, 85, 43, 2, 28, 99, 67, 1.98, 33, 19, 17, 44 };
SortedList <double, double> monitor = new SortedList <double, double>();
q = new MinPriorityQueue <double>(7);
for (int i = 0; i < items.Length; i++)
{
q.Enqueue(items[i]);
monitor.Add(items[i], items[i]);
}
q.Remove(43);
monitor.Remove(43);
q.Remove(17);
monitor.Remove(17);
foreach (double monitorItem in monitor.Values)
{
Assert.AreEqual(monitorItem, q.Dequeue());
}
}
public void Test_Integration_2()
{
PriorityQueue <double> q = null;
double[] items = { 82, 100, 9.3, 1.19, 10, 29, 12, 9.0006, 22, 20.9, 207, 13.56, 30, 2, 66 };
SortedList <double, double> monitor = new SortedList <double, double>();
q = new MinPriorityQueue <double>();
for (int i = 0; i < items.Length; i++)
{
q.Enqueue(items[i]);
monitor.Add(items[i], items[i]);
if (i == 3)
{
q.Dequeue();
monitor.Remove(1.19);
}
else if (i == 8)
{
q.Dequeue();
monitor.Remove(9.0006);
}
}
foreach (double monitorItem in monitor.Values)
{
Assert.AreEqual(monitorItem, q.Dequeue());
}
}
/// <summary>
/// The Dijkstra's algorithm.
/// </summary>
private void _dijkstra()
{
while (!_minPriorityQueue.IsEmpty)
{
var currentVertex = _minPriorityQueue.DequeueMin();
var currentVertexIndex = _nodesToIndices[currentVertex];
var outgoingEdges = _graph.OutgoingEdges(currentVertex);
foreach (var outgoingEdge in outgoingEdges)
{
var adjacentIndex = _nodesToIndices[outgoingEdge.Destination];
var delta = _distances[currentVertexIndex] != Infinity ? _distances[currentVertexIndex] + outgoingEdge.Weight : Infinity;
if (delta < _distances[adjacentIndex])
{
_distances[adjacentIndex] = delta;
_predecessors[adjacentIndex] = currentVertexIndex;
if (_minPriorityQueue.Contains(outgoingEdge.Destination))
{
_minPriorityQueue.UpdatePriority(outgoingEdge.Destination, delta);
}
else
{
_minPriorityQueue.Enqueue(outgoingEdge.Destination, delta);
}
}
}
}
}
private void _initialize()
{
var verticesCount = _graph.VerticesCount;
_distances = new long[verticesCount];
_predecessors = new int[verticesCount];
_nodesToIndices = new Dictionary <TVertex, int>();
_indicesToNodes = new Dictionary <int, TVertex>();
_minPriorityQueue = new MinPriorityQueue <TVertex, long>((uint)verticesCount);
var vertices = _graph.Vertices.ToList();
for (int i = 0; i < verticesCount; i++)
{
if (_source.Equals(vertices[i]))
{
_distances[i] = 0;
_predecessors[i] = 0;
}
else
{
_distances[i] = Infinity;
_predecessors[i] = NilPredecessor;
}
_minPriorityQueue.Enqueue(vertices[i], _distances[i]);
_nodesToIndices.Add(vertices[i], i);
_indicesToNodes.Add(i, vertices[i]);
}
}
public void Dequeue_Should_Always_Return_The_Min_Value()
{
var pq = new MinPriorityQueue <int>();
pq.Enqueue(6);
pq.Enqueue(9);
pq.Enqueue(8);
pq.Enqueue(3);
pq.Enqueue(5);
pq.Enqueue(1);
pq.Enqueue(3);
pq.Count.Should().Be(7);
pq.Dequeue().Should().Be(1);
pq.Count.Should().Be(6);
pq.Dequeue().Should().Be(3);
pq.Count.Should().Be(5);
pq.Dequeue().Should().Be(3);
pq.Count.Should().Be(4);
pq.Dequeue().Should().Be(5);
pq.Count.Should().Be(3);
pq.Dequeue().Should().Be(6);
pq.Count.Should().Be(2);
pq.Dequeue().Should().Be(8);
pq.Count.Should().Be(1);
pq.Dequeue().Should().Be(9);
pq.Count.Should().Be(0);
}
public void Enqueue_Should_Add_Item_To_An_Empty_Queue()
{
var pq = new MinPriorityQueue <int>();
pq.Enqueue(10);
pq.IsEmpty.Should().BeFalse();
pq.Count.Should().Be(1);
}
private static MinPriorityQueue <int> CreateQueue(int[] priorities)
{
var queue = new MinPriorityQueue <int>(priorities.Length, int.MaxValue);
for (var i = 0; i < priorities.Length; i++)
{
queue.Enqueue(i, priorities[i]);
}
return(queue);
}
public static IEnumerable <Edge <T> > DijkstraShortestPath <T>(this IGraph <T> graph, T startVertex, T finishVertex) where T : IEquatable <T>
{
var currentVertex = startVertex;
var weigths = new MinPriorityQueue <Weight <T> >();
var paths = new Dictionary <T, Path <T> >
{
{ startVertex, new Path <T> {
Weight = 0.0, Edges = new List <Edge <T> >()
} }
};
while (paths.Count < graph.VertexCount)
{
foreach (var edge in graph.EdgesOf(currentVertex))
{
if (edge.Weight < 0)
{
throw new ArgumentOutOfRangeException(
"Edge.Weight", edge.Weight,
"Dijkstra's algorithm for shortest paths does not support negative weights.");
}
if (!paths.ContainsKey(edge.Target))
{
weigths.Enqueue(new Weight <T>
{
Edge = edge,
PathWeight = paths[edge.Source].Weight + edge.Weight
});
}
}
Weight <T> smallest;
do
{
// skip obsolete edges
smallest = weigths.DequeueMin();
} while (paths.ContainsKey(smallest.Edge.Target));
var pathToSource = paths[smallest.Edge.Source];
var path = new List <Edge <T> >(pathToSource.Edges);
path.Add(smallest.Edge);
if (smallest.Edge.Target.Equals(finishVertex))
{
return(path);
}
currentVertex = smallest.Edge.Target;
paths.Add(smallest.Edge.Target, new Path <T> {
Weight = smallest.PathWeight, Edges = path
});
}
return(new Edge <T> [0]);
}
public void MinQueueAddItemWithSize()
{
var queue = new MinPriorityQueue <string, int>(Number);
for (int i = 0; i < _array.Length; i++)
{
queue.Enqueue(_array[i].Item1, _array[i].Item2);
}
Assert.AreEqual(Number, queue.Count);
}
//Placeholder, full game would have units stored elsewhere
public void UnitInit()
{
PlayerUnit adam = new PlayerUnit(
84,
"Adam",
"The Bearded Buddy",
422,
2,
69,
7,
0,
4,
98,
20,
0,
87,
0);
playerUnits.Add(adam);
turnQueue.Enqueue(adam, defaultTurnSpeed);
PlayerUnit dylan = new PlayerUnit(
2,
"Dylan",
"Probably an Alien",
999,
2,
80,
70,
10,
0,
1,
47,
10,
77,
0);
playerUnits.Add(adam);
turnQueue.Enqueue(adam, defaultTurnSpeed);
}
public void Dequeue_ShouldRemoveTheSmallestItem()
{
var items = new List <char> {
'T', 'Z', 'B'
};
var target = new MinPriorityQueue <char>();
items.ForEach(anItem => target.Enqueue(anItem));
items.Sort();
Assert.That(target.Dequeue(), Is.EqualTo(items[0]));
}
public void ReplacingMinElementAndCheckingIfExtractedInSortedOrder()
{
var pq = new MinPriorityQueue <int, int>();
int maxHeapElement = 50000;
int minHeapElement = -50000;
int addedElements = 0;
//Adding every seventh number, then every fifth number,
//every third and at last all numbers
//NOTE: some items are added more than once
for (int i = 7; i > 0; i -= 2)
{
int el = minHeapElement;
while (el <= maxHeapElement)
{
pq.Enqueue(el, -el);
addedElements++;
el += i;
}
}
if (pq.Count != addedElements)
{
Assert.Fail();
}
pq.ReplaceFirst(int.MaxValue, -int.MaxValue);
pq.ReplaceFirst(int.MaxValue, -int.MaxValue);
pq.ReplaceFirst(int.MaxValue, -int.MaxValue);
int removedElements = 0;
var min = pq.Peek();
while (!pq.IsEmpty)
{
var kvp = pq.Peek();
if (min.Key > kvp.Key)
{
Assert.Fail();
}
min = pq.Dequeue();
removedElements++;
}
Assert.IsTrue(pq.IsEmpty &&
pq.Count == 0 &&
addedElements == removedElements);
}
public void DequeueMinValue()
{
var sut = new MinPriorityQueue <int, int>();
for (var i = 0; i < 50000; i++)
{
sut.Enqueue(i, i);
}
for (var i = 0; i < 50000; i++)
{
Assert.AreEqual(i, sut.Dequeue());
}
}
public void AddingElementsWithCustomComparerAndCheckingIfExtractedInSortedOrder()
{
//Creating heap with reversed comparer
var pq = new MinPriorityQueue <int, int>(Comparer <int> .Create(
(x, y) => y.CompareTo(x)));
int maxHeapElement = 50000;
int minHeapElement = -50000;
int addedElements = 0;
//Adding every seventh number, then every fifth number,
//every third and at last all numbers
//NOTE: some items are added more than once
for (int i = 7; i > 0; i -= 2)
{
int el = minHeapElement;
while (el <= maxHeapElement)
{
pq.Enqueue(el, -el);
addedElements++;
el += i;
}
}
if (pq.Count != addedElements)
{
Assert.Fail();
}
int removedElements = 0;
// because of the reversed comparer
var max = pq.Peek();
while (!pq.IsEmpty)
{
var kvp = pq.Peek();
if (max.Key < kvp.Key)
{
Assert.Fail();
}
max = pq.Dequeue();
removedElements++;
}
Assert.IsTrue(pq.IsEmpty &&
pq.Count == 0 &&
addedElements == removedElements);
}
private static void Main()
{
var maxPriorityQueue = new MaxPriorityQueue <string>();
maxPriorityQueue.Enqueue("Buy bread", 15);
maxPriorityQueue.Enqueue("Buy milk", 10);
maxPriorityQueue.Enqueue("Buy chocolate", 17);
maxPriorityQueue.Enqueue("Go to shop", 30);
maxPriorityQueue.Enqueue("Go home", 9);
Console.WriteLine("Max priority queue: ");
maxPriorityQueue.PrintQueue();
var minPriorityQueue = new MinPriorityQueue <string>();
minPriorityQueue.Enqueue("Buy bread", 15);
minPriorityQueue.Enqueue("Buy milk", 10);
minPriorityQueue.Enqueue("Buy chocolate", 17);
minPriorityQueue.Enqueue("Go to shop", 30);
minPriorityQueue.Enqueue("Go home", 9);
Console.WriteLine("Min priority queue: ");
minPriorityQueue.PrintQueue();
}
public void MinPriorityQueue_SingleEnqueueDequeueTest()
{
string test = "test";
var queue = new MinPriorityQueue <string>();
queue.Enqueue(test);
Assert.IsFalse(queue.IsEmpty);
Assert.AreEqual(1, queue.Size);
var dequeued = queue.DequeueMin();
Assert.IsTrue(queue.IsEmpty);
Assert.AreEqual(0, queue.Size);
Assert.AreEqual(test, dequeued);
}
public void MinPriorityQueue_Enqueue()
{
int capacity = 5;
var q = new MinPriorityQueue<Element>(capacity);
for (int i = capacity; i > 0; i--)
{
q.Enqueue(new Element { Number = i, Data = new byte[i]});
}
Assert.IsTrue(q.Size == capacity);
for (int i = 1; i <= capacity; i++)
{
var e = q.Dequeue();
Assert.IsTrue(i == e.Number);
}
}
/// <summary>
/// Runs MinMax on a unit.
/// </summary>
/// <returns>A result-UnitAction pair.</returns>
private KeyValuePair<Result, UnitAction> MinMax()
{
List<Node.NodePointer> targets = pathManager.getCurrentTargets(subjectRef);
MinPriorityQueue<UnitAction> bestMoves = new MinPriorityQueue<UnitAction>();
int realclay = subjectRef.getClay();
// The "max-y" part: maximize (damage/counter-damage)
foreach (Node.NodePointer candidateAttackTarget in targets)
{
int moveCost = candidateAttackTarget.getDist();
Unit curEnemy = candidateAttackTarget.getTarget().Occupier;
AttackRound util = new AttackRound(subjectRef, moveCost, curEnemy);
UnitAction roundMove = new UnitAction(subjectRef, curEnemy, candidateAttackTarget.getStart());
int totDmg = 0;
// Will very likely die, enqueue this move as bad, and don't move to next step.
//TODO: utility = 0
if (util.attackerDies() || util.getUtility() == 0)
{
bestMoves.Enqueue(roundMove, double.PositiveInfinity);
util.resetBack();
subjectRef.setClay(realclay);
continue;
}
totDmg += util.getExpectedDamage();
// Loop through all things that could attack this position, and continue testing attacks.
// The "min-y" part. Enemy tries to maximize their (damage/counter-damage)
// Technically could just do damage maximization, since counter-damage is fixed.
foreach (Unit enemy in subjectsEnemiesRef)
{
if (enemy.getClay() > 0 && pathManager.canAttack(enemy, candidateAttackTarget.getStart()))
{
//gets the closest move. This will be the move that maxes damage.
int enemyMoveCost = pathManager.maxDamageMoveCost(enemy, candidateAttackTarget.getStart());
AttackRound subRound = new AttackRound(enemy, enemyMoveCost, subjectRef);
int roundClay = subjectRef.getClay();
subRound.resetBack();
subjectRef.setClay(roundClay);
// If we die, break early, as usual.
if (util.defenderDies())
{
break;
}
totDmg += subRound.getExpectedCounterDamage();
}
}
// Died. Enqueue with +inf again.
if (subjectRef.getClay() == 0)
bestMoves.Enqueue(roundMove, double.PositiveInfinity);
// enqueue move! min pri queue, so invert answer.
else
bestMoves.Enqueue(roundMove, -((double)totDmg / subjectRef.getClay()));
util.resetBack();
subjectRef.setClay(realclay);
}
subjectRef.setClay(realclay);
// no local targets...
if (bestMoves.Count == 0)
return new KeyValuePair<Result, UnitAction>(Result.NothingFound, null);
// all moves die. only move is not to play.
else if (bestMoves.currentInversePriority(bestMoves.Peek()) == double.PositiveInfinity)
return new KeyValuePair<Result, UnitAction>(Result.WillDie, bestMoves.Peek());
// found good target.
return new KeyValuePair<Result, UnitAction>(Result.Success, bestMoves.Peek());
}
/// <summary>
/// Returns a sorted list of nodes within a given endurance value.
/// Performs a Dijkstra-like algorithm.
/// </summary>
/// <param name="satifies">The predicate each node must follow.</param>
/// <param name="endurance">The maximum endurance to follow out.</param>
/// <returns>A sorted list of nodes within a given endurance value.</returns>
public List<Node> nodesThatSatisfyPred(Node startNode, System.Predicate<Node> satifies, float endurance = 16.0f, bool stopOnFirst = false, bool isPathfinding = true)
{
List<Node> foundNodes = new List<Node>();
MinPriorityQueue<Node> nodeList = new MinPriorityQueue<Node>();
initializePathfinding(isPathfinding);
startNode.realCost = 0;
nodeList.Enqueue(startNode, startNode.realCost);
#if DEBUG_PATHFINDER_LOGDEBUG
StringBuilder encountered = new StringBuilder();
StringBuilder nodes = new StringBuilder();
nodes.Append("Start node ").Append(startNode.Number).AppendLine();
encountered.Append("Start node ").Append(startNode.Number).AppendLine();
encountered.Append("endurance = ").Append(endurance).AppendLine();
#endif
while (nodeList.Count > 0)
{
//Pick the best looking node, by f-value.
Node best = nodeList.Dequeue();
double bestDist = best.realCost;
#if DEBUG_PATHFINDER_LOGDEBUG
encountered.Append("Node ").Append(best.Number).Append(" ").Append(best).AppendLine();
nodes.Append("Node ").Append(best.Number).AppendLine();
#endif
best.Visited = true;
if (satifies(best))
{
foundNodes.Add(best);
if (stopOnFirst)
return foundNodes;
}
//string updateString = "updating: ";
foreach (Edge e in best.getEdges())
{
Node other = e.getNode();
//We already visited this node, move along,
if (other.Visited)
continue;
//Tentative distance.
double testDist = e.getWeight() + bestDist;
if (testDist > endurance)
continue;
//If the other node isn't in the priority queue, add it.
if (!nodeList.Contains(other))
{
other.CameFrom = best;
other.realCost = testDist;
nodeList.Enqueue(other, other.realCost);
#if DEBUG_PATHFINDER_LOGDEBUG
encountered.Append(" added ").Append(other.Number)
.Append(", total estimated cost ")
.Append(other.realCost).AppendLine();
#endif
continue;
}
//If the other node was a bad path, and this one's better, replace it.
else if (other.realCost > testDist)
{
other.CameFrom = best;
other.realCost = testDist;
nodeList.Update(other, other.realCost);
#if DEBUG_PATHFINDER_LOGDEBUG
encountered.Append(" updated ").Append(other.Number)
.Append(", total new estimated cost ")
.Append(other.realCost).AppendLine();
#endif
}
}
}
#if DEBUG_PATHFINDER_LOGDEBUG
Debug.Log(encountered);
Debug.Log(nodes);
#endif
return foundNodes;
}
protected virtual Stack<PathNode> AStar(Tile source, Tile destination)
{
List<Tile> closed = new List<Tile>();
List<Tile> toDetermine;
List<Tile> toAdd = new List<Tile>();
Stack<PathNode> finalPath = null;
MinPriorityQueue<PathNode> open = new MinPriorityQueue<PathNode>();
List<PathNode> openList = new List<PathNode>();
open.Enqueue(new PathNode(source, destination));
openList.Add(open.Peek());
PathNode currentNode = null;
bool endReached = false;
do
{
currentNode = open.Dequeue();
openList.Remove(currentNode);
if (currentNode.HCost == 0)
{
endReached = true;
finalPath = currentNode.GetPath();
}
else
{
closed.Add(tiles[currentNode.Current.X, currentNode.Current.Y]);
toDetermine = getAdjacent(currentNode);
foreach (Tile t in toDetermine)
{
bool remove = false;
if (t.Collision > source.Unit.Collision)
remove = true;
if (t.HasUnit())
if (t.Unit.Army != source.Unit.Army) //added so that AI works
remove = true;
if (closed.Contains(t))
remove = true;
//Add this if I want to have no duplicate pathnodes (currently,
//multiple exist with different source nodes
/*
PathNode temp = new PathNode(t.GridwiseLocation, currentNode, destination.GridwiseLocation);
foreach (PathNode p in openList)
{
if (p.Current == temp.Current)
{
if (p.GCost > temp.GCost)
{
p.Source = temp.Source;
remove = true;
}
}
}'*/
if (!remove)
toAdd.Add(t);
}
foreach (Tile t in toAdd)
{
PathNode temp = new PathNode(t.GridwiseLocation, currentNode, destination.GridwiseLocation);
open.Enqueue(temp);
}
toAdd.Clear();
}
} while (!endReached);
return finalPath;
}
// run away to the node that's farthest away from all enemies.
private KeyValuePair<Result, UnitAction> RunAway()
{
MinPriorityQueue<UnitAction> farthestActions = new MinPriorityQueue<UnitAction>();
foreach (Node n in pathManager.getAccessibleNodes(subjectRef))
{
int curCount = 0;
foreach (Unit en in subjectsEnemiesRef)
curCount += Node.range(n, en.getNode());
// min priority queue: negate results.
UnitAction runAwayTo = new UnitAction(subjectRef, null, n);
farthestActions.Enqueue(runAwayTo, -curCount);
}
if (farthestActions.Count == 0)
return new KeyValuePair<Result, UnitAction>(Result.NothingFound, UnitAction.DoNothing(subjectRef));
else
return new KeyValuePair<Result, UnitAction>(Result.Success, farthestActions.Dequeue());
}
/// <summary>
/// A* on the graph.
/// </summary>
/// <param name="pathStoreLoc">The Queue to store the path in.</param>
/// <param name="start">The starting node.</param>
/// <param name="end">The ending node.</param>
public double AStar(Queue<Node> pathStoreLoc, Node start, Node end, Node toIgnore = null)
{
MinPriorityQueue<Node> nodeList = new MinPriorityQueue<Node>();
initializePathfinding(true);
if (toIgnore != null)
toIgnore.Visited = false;
System.Func<Node, Node, float> Heuristic;
if (allowedPaths == Paths.quadDir)
Heuristic = ManhattenHeuristic;
else if (allowedPaths == Paths.octDir)
Heuristic = DiagonalHeuristic;
else
Heuristic = DiagonalHeuristic;
start.CameFrom = null;
start.heuristicCost = Heuristic(start, end);
start.realCost = 0;
nodeList.Enqueue(start, start.heuristicCost);
#if DEBUG_PATHFINDER_LOGDEBUG
StringBuilder encountered = new StringBuilder();
StringBuilder nodes = new StringBuilder();
nodes.Append("Start node ").Append(start.Number).AppendLine();
encountered.Append("Start node ").Append(start.Number).AppendLine();
nodes.Append("End node ").Append(end.Number).AppendLine();
encountered.Append("End node ").Append(end.Number).AppendLine();
#endif
while (nodeList.Count > 0)
{
//Pick the best looking node, by f-value.
Node best = nodeList.Dequeue();
double bestDist = best.realCost;
#if DEBUG_PATHFINDER_LOGDEBUG
encountered.Append("Node ").Append(best.Number).Append(" ").Append(best).AppendLine();
nodes.Append("Node ").Append(best.Number).AppendLine();
#endif
//If this is the end, stop, show the path, and return it.
if (best.Equals(end))
{
ReconstructPath(pathStoreLoc, end);
ShowPath(pathStoreLoc);
#if DEBUG_PATHFINDER_LOGDEBUG
encountered.Append("Finished!\n\nFinal dist: ")
.Append(best.realCost).AppendLine();
Debug.Log(encountered);
Debug.Log(nodes);
#endif
return best.realCost;
}
best.Visited = true;
//string updateString = "updating: ";
foreach (Edge e in best.getEdges())
{
Node other = e.getNode();
//We already visited this node, move along,
if (other.Visited)
continue;
//Tentative distance.
double testDist = e.getWeight() + bestDist;
//If the other node isn't in the priority queue, add it.
if (!nodeList.Contains(other))
{
other.CameFrom = best;
other.realCost = testDist;
other.heuristicCost = Heuristic(other, end);
nodeList.Enqueue(other, other.realCost + other.heuristicCost);
#if DEBUG_PATHFINDER_LOGDEBUG
encountered.Append(" added ").Append(other.Number)
.Append(", total estimated cost ")
.Append(other.realCost + other.heuristicCost)
.AppendLine();
#endif
continue;
}
//If the other node was a bad path, and this one's better, replace it.
else if (other.realCost > testDist)
{
other.CameFrom = best;
other.realCost = testDist;
nodeList.Update(other, other.realCost + other.heuristicCost);
#if DEBUG_PATHFINDER_LOGDEBUG
encountered.Append(" updated ").Append(other.Number)
.Append(", total new estimated cost ")
.Append(other.realCost + other.heuristicCost)
.AppendLine();
#endif
}
}
}
#if DEBUG_PATHFINDER_LOGDEBUG
encountered.Append("Failed!\n");
Debug.Log(encountered);
Debug.Log(nodes);
#endif
return double.PositiveInfinity;
}