private void initialize(IEnumerable <Line> lineSegments)
{
SweepLine = new Line(new Point(0, 0), new Point(0, int.MaxValue), Tolerance);
currentlyTrackedLines = new RedBlackTree <Event>(true, pointComparer);
intersectionEvents = new Dictionary <Point, HashSet <Tuple <Event, Event> > >(pointComparer);
verticalHorizontalLines = new HashSet <Event>();
normalLines = new HashSet <Event>();
rightLeftEventLookUp = lineSegments
.Select(x =>
{
if (x.Left.X < 0 || x.Left.Y < 0 || x.Right.X < 0 || x.Right.Y < 0)
{
throw new Exception("Negative coordinates are not supported.");
}
return(new KeyValuePair <Event, Event>(
new Event(x.Left, pointComparer, EventType.Start, x, this),
new Event(x.Right, pointComparer, EventType.End, x, this)
));
}).ToDictionary(x => x.Value, x => x.Key);
eventQueueLookUp = new HashSet <Event>(rightLeftEventLookUp.SelectMany(x => new[] {
x.Key,
x.Value
}), new PointComparer());
eventQueue = new BMinHeap <Event>(eventQueueLookUp, new EventQueueComparer());
}
/// <summary>
/// Returns a dictionary of chosen encoding bytes for each distinct T
/// </summary>
/// <param name="input"></param>
/// <returns></returns>
public Dictionary <T, byte[]> Compress(T[] input)
{
var frequencies = computeFrequency(input);
var minHeap = new BMinHeap <FrequencyWrap>();
foreach (var frequency in frequencies)
{
minHeap.Insert(new FrequencyWrap(
frequency.Key, frequency.Value));
}
while (minHeap.Count > 1)
{
var a = minHeap.ExtractMin();
var b = minHeap.ExtractMin();
var newNode = new FrequencyWrap(
default(T), a.Frequency + b.Frequency);
newNode.Left = a;
newNode.Right = b;
minHeap.Insert(newNode);
}
var root = minHeap.ExtractMin();
var result = new Dictionary <T, byte[]>();
DFS(root, new List <byte>(), result);
return(result);
}
/// <summary>
/// Sort the given input
/// where elements are misplaced almost by a distance k
/// </summary>
/// <param name="input"></param>
/// <param name="k"></param>
/// <returns></returns>
public static int[] Sort(int[] input, int k)
{
if (k > input.Length)
{
throw new Exception("K cannot exceed array length.");
}
var firstKElements = new int[k];
Array.Copy(input, firstKElements, k);
var minHeap = new BMinHeap <int>(firstKElements);
var result = new List <int>();
for (int i = k; i < input.Length; i++)
{
result.Add(minHeap.ExtractMin());
minHeap.Insert(input[i]);
}
while (minHeap.Count > 0)
{
result.Add(minHeap.ExtractMin());
}
return(result.ToArray());
}
public void BMinHeap_Test()
{
var rnd = new Random();
var initial = Enumerable.Range(0, 51).OrderBy(x => rnd.Next()).ToList();
//insert test
var tree = new BMinHeap <int>(initial);
for (int i = 51; i <= 99; i++)
{
tree.Insert(i);
}
for (int i = 0; i <= 99; i++)
{
var min = tree.ExtractMin();
Assert.AreEqual(min, i);
}
var testSeries = Enumerable.Range(1, 49).OrderBy(x => rnd.Next()).ToList();
foreach (var item in testSeries)
{
tree.Insert(item);
}
for (int i = 1; i <= 49; i++)
{
var min = tree.ExtractMin();
Assert.AreEqual(min, i);
}
}
private void initialize(IEnumerable <Line> lineSegments)
{
SweepLine = new Line(new Point(0, 0), new Point(0, int.MaxValue), Tolerance);
var pointComparer = new PointComparer(Tolerance);
currentlyTracked = new RedBlackTree <Event>(true, pointComparer);
intersectionEvents = new Dictionary <Point, HashSet <Tuple <Event, Event> > >(pointComparer);
specialLines = new HashSet <Event>();
normalLines = new HashSet <Event>();
rightLeftEventLookUp = lineSegments
.Select(x =>
{
return(new KeyValuePair <Event, Event>(
new Event(x.Left, EventType.Start, x, this),
new Event(x.Right, EventType.End, x, this)
));
}).ToDictionary(x => x.Value, x => x.Key);
eventQueueLookUp = new HashSet <Event>(rightLeftEventLookUp.SelectMany(x => new[] {
x.Key,
x.Value
}), new PointComparer(Tolerance));
eventQueue = new BMinHeap <Event>(eventQueueLookUp, new EventQueueComparer(Tolerance));
}
/// <summary>
/// Do DFS to pick smallest weight neighbour edges
/// of current spanning tree one by one
/// </summary>
/// <param name="graph"></param>
/// <param name="currentVertex"></param>
/// <param name="spanTreeVertices"></param>
/// <param name="spanTreeNeighbours"> Use Fibornacci Min Heap to pick smallest edge neighbour </param>
/// <param name="spanTreeEdges">result MST edges</param>
private void DFS(WeightedGraph <T, W> graph,
WeightedGraphVertex <T, W> currentVertex,
BMinHeap <MSTEdge <T, W> > spanTreeNeighbours,
HashSet <T> spanTreeVertices,
List <MSTEdge <T, W> > spanTreeEdges)
{
//add all edges to Fibornacci Heap
//So that we can pick the min edge in next step
foreach (var edge in currentVertex.Edges)
{
spanTreeNeighbours.Insert(new MSTEdge <T, W>(
currentVertex.Value,
edge.Key.Value, edge.Value));
}
//pick min edge
var minNeighbourEdge = spanTreeNeighbours.ExtractMin();
//skip edges already in MST
while (spanTreeVertices.Contains(minNeighbourEdge.Source) &&
spanTreeVertices.Contains(minNeighbourEdge.Destination))
{
minNeighbourEdge = spanTreeNeighbours.ExtractMin();
//if no more neighbours to explore
//time to end exploring
if (spanTreeNeighbours.Count == 0)
{
return;
}
}
//keep track of visited vertices
//do not duplicate vertex
if (!spanTreeVertices.Contains(minNeighbourEdge.Source))
{
spanTreeVertices.Add(minNeighbourEdge.Source);
}
//Destination vertex will never be a duplicate
//since this is an unexplored Vertex
spanTreeVertices.Add(minNeighbourEdge.Destination);
//add edge to result
spanTreeEdges.Add(minNeighbourEdge);
//now explore the destination vertex
DFS(graph, graph.Vertices[minNeighbourEdge.Destination],
spanTreeNeighbours, spanTreeVertices, spanTreeEdges);
}
/// <summary>
/// Time complexity: O(nlog(n)).
/// </summary>
public static T[] Sort(T[] array)
{
//heapify
var heap = new BMinHeap <T>(array);
//now extract min until empty and return them as sorted array
var sortedArray = new T[array.Length];
var j = 0;
while (heap.Count > 0)
{
sortedArray[j] = heap.ExtractMin();
j++;
}
return(sortedArray);
}
/// <summary>
/// Find smallest by first constructing a BMinHeap in O(n) time
/// & then extracting out k -1 times
/// Finally do one more extract to return the kth smallest
/// Total O(n+k) complexity
/// Better algorithms do exist with O(n) time
/// </summary>
/// <param name="input"></param>
/// <param name="k"></param>
/// <returns></returns>
public T FindKthSmallest(T[] input, int k)
{
if (k > input.Length)
{
throw new Exception("K exceeds input length.");
}
var minHeap = new BMinHeap <T>(input);
//0,1,2...(k-1) min extraction
for (int i = 0; i < k - 1; i++)
{
minHeap.ExtractMin();
}
//kth extraction
return(minHeap.ExtractMin());
}
//O(nlog(n))
public static T[] Sort(T[] array)
{
//heapify
var heap = new BMinHeap <T>();
for (int i = 0; i < array.Length; i++)
{
heap.Insert(array[i]);
}
//now extract min until empty and return them as sorted array
var sortedArray = new T[array.Length];
int j = 0;
while (heap.Count > 0)
{
sortedArray[j] = heap.ExtractMin();
j++;
}
return(sortedArray);
}
