/// <summary>
/// Computes the shortest path from u to v in the map.
/// </summary>
/// <param name="u"></param>
/// <param name="v"></param>
/// <param name="map"></param>
/// <param name="paths"></param>
/// <returns></returns>
private decimal ShortestPath(string u, string v, DirectedGraph <string, decimal> map, out Dictionary <string, string> paths)
{
paths = new Dictionary <string, string>();
MinPriorityQueue <decimal, Edge <string, decimal> > queue = new MinPriorityQueue <decimal, Edge <string, decimal> >();
paths.Add(u, u);
if (u.Equals(v))
{
return(0);
}
foreach (Edge <string, decimal> i in map.OutgoingEdges(u))
{
queue.Add(i.Data, i);
}
while (queue.Count > 0)
{
decimal priority = queue.MinimumPriority;
Edge <string, decimal> temp = queue.RemoveMinimumPriority();
if (!paths.ContainsKey(temp.Destination))
{
paths.Add(temp.Destination, temp.Source);
if (temp.Destination == v)
{
return(priority);
}
foreach (Edge <string, decimal> i in map.OutgoingEdges(temp.Destination))
{
queue.Add(priority + i.Data, i);
}
}
}
return(-1);
}
/// <summary>
/// Returns the shortest paths
/// </summary>
/// <param name="u">generic string</param>
/// <param name="v">generic string</param>
/// <param name="map">DirectedGraph map</param>
/// <param name="paths">Dictionary paths</param>
/// <returns></returns>
private decimal ShortestPath(string u, string v, DirectedGraph <string, decimal> map, out Dictionary <string, string> paths)
{
paths = new Dictionary <string, string>();
MinPriorityQueue <decimal, Edge <string, decimal> > tempQueue = new MinPriorityQueue <decimal, Edge <string, decimal> >();
paths.Add(u, u);
if (u.Equals(v))
{
return(0);
}
foreach (Edge <string, decimal> outGoEdge in map.OutgoingEdges(u))
{
tempQueue.Add(outGoEdge.Data, outGoEdge);
}
while (tempQueue.Count > 0) //possibly wrong
{
decimal p = tempQueue.MinimumPriority;
Edge <string, decimal> edgeRemoved = tempQueue.RemoveMinimumPriority();
if (!paths.ContainsKey(edgeRemoved.Destination))
{
paths.Add(edgeRemoved.Destination, edgeRemoved.Source);
if (edgeRemoved.Destination.Equals(v))
{
return(p);
}
foreach (Edge <string, decimal> outGoEdge in map.OutgoingEdges(edgeRemoved.Destination))
{
tempQueue.Add(p + outGoEdge.Data, outGoEdge);
}
}
}
return(-1);
}
/// <summary>
/// Finds a shortest path from the given start node to the given end node in the given graph.
/// </summary>
/// <param name="u">The start node.</param>
/// <param name="v">The end node.</param>
/// <param name="map">The graph.</param>
/// <param name="paths">The resulting shortest paths.</param>
/// <returns>The length of the shortest path.</returns>
private decimal ShortestPath(string u, string v, DirectedGraph <string, decimal> map,
out Dictionary <string, string> paths)
{
paths = new Dictionary <string, string>();
MinPriorityQueue <decimal, Edge <string, decimal> > pq = new MinPriorityQueue <decimal, Edge <string, decimal> >();
paths.Add(u, u);
if (u == v)
{
return(0);
}
foreach (Edge <string, decimal> e in map.OutgoingEdges(u))
{
pq.Add(e, e.Data);
}
while (pq.Count > 0)
{
decimal p = pq.MininumPriority;
Edge <string, decimal> e = pq.RemoveMinimumPriority();
if (!paths.ContainsKey(e.Destination))
{
paths.Add(e.Destination, e.Source);
if (e.Destination == v)
{
return(p);
}
foreach (Edge <string, decimal> outgoing in map.OutgoingEdges(e.Destination))
{
pq.Add(outgoing, p + outgoing.Data);
}
}
}
return(-1);
}
public void TestJMinimumPriority()
{
MinPriorityQueue <int, string> pq = new MinPriorityQueue <int, string>();
pq.Add(5, "five");
pq.Add(2, "two");
pq.Add(6, "six");
Assert.That(pq.MinimumPriority, Is.EqualTo(2));
}
public void TestKCountAfterRemove()
{
MinPriorityQueue <int, string> pq = new MinPriorityQueue <int, string>();
pq.Add(5, "five");
pq.Add(2, "two");
pq.Add(6, "six");
pq.RemoveMinimumPriority();
Assert.That(pq.Count, Is.EqualTo(2));
}
public void TestJRemoveMinimumPriority()
{
MinPriorityQueue <int, string> pq = new MinPriorityQueue <int, string>();
pq.Add(5, "five");
pq.Add(2, "two");
pq.Add(6, "six");
string s = pq.RemoveMinimumPriority();
Assert.That(s, Is.EqualTo("two"));
}
// Implementation of Dijkstra's Algorithm
public List <Tile> FindPath(Tile start, Tile end)
{
MinPriorityQueue <Tile, int> queue = new MinPriorityQueue <Tile, int>();
// from prev tile to cur tile dictionary
Dictionary <Tile, Tile> prev = new Dictionary <Tile, Tile>();
foreach (Tile t in tiles)
{
if (!t.IsWalkable && t != start)
{
continue;
}
queue.Add(t, int.MaxValue);
prev.Add(t, null);
}
queue.Add(start, 0);
while (queue.Count > 0)
{
int uDist;
Tile u = queue.Pop(out uDist);
foreach (Tile v in u.neighborTiles)
{
if (!queue.Contains(v))
{
continue;
}
int vDist = uDist + 1;
if (vDist < queue.GetValue(v))
{
queue.Add(v, vDist);
prev[v] = u;
}
}
}
Tile cur = prev[end];
List <Tile> path = new List <Tile>();
while (cur != null)
{
path.Insert(0, cur);
cur = prev[cur];
}
return(path);
}
/// <summary>
/// Finds a shortest path from the given start node to the given end node in the given graph.
/// </summary>
/// <param name="u">The start node.</param>
/// <param name="v">The end node.</param>
/// <param name="map">The graph.</param>
/// <param name="paths">The resulting shortest paths.</param>
/// <returns>The length of the shortest path.</returns>
private decimal ShortestPath(string u, string v, DirectedGraph <string, decimal> map, out Dictionary <string, string> paths)
{
//throw new NotImplementedException();
paths = new Dictionary <string, string>();
paths.Add(u, u);
if (u == v)
{
return(0);
}
MinPriorityQueue <decimal, Tuple <string, string> > q = new MinPriorityQueue <decimal, Tuple <string, string> >();
//add all outgoing edges from u
foreach (Tuple <string, decimal> edge in map.OutgoingEdges(u))
{
//add this edge to priority queue
q.Add(new Tuple <string, string>(u, edge.Item1), edge.Item2);
}
while (q.Count != 0)
{
decimal priority = q.MininumPriority;
Tuple <string, string> edge = q.RemoveMinimumPriority();
string x = edge.Item1;
string w = edge.Item2;
if (!paths.ContainsKey(w))
{
paths.Add(w, x);
if (w == v)
{
return(priority);
}
else
{
foreach (Tuple <string, decimal> edge2 in map.OutgoingEdges(w))
{
q.Add(new Tuple <string, string>(w, edge2.Item1), edge2.Item2 + priority);
}
}
}
}
return(-1);
}
public void AddNum(int num)
{
if (maxHeap.Count == 0 || num < maxHeap.Max)
{
maxHeap.Add(num);
}
else
{
minHeap.Add(num);
}
if (maxHeap.Count < minHeap.Count)
{
maxHeap.Add(minHeap.DeleteMin());
}
else if (maxHeap.Count > minHeap.Count + 1)
{
minHeap.Add(maxHeap.DeleteMax());
}
}
public void Add(Node node)
{
if (Contains(node))
{
return;
}
hashSet.Add(node);
openSet.Add(node.TotalCost, node);
CallEvent(node);
_count++;
}
/// <summary>
/// Builds a Huffman tree from the given leaves.
/// </summary>
/// <param name="q">A min-priority queue containing the leaves of a Huffman tree. The priority of each leaf is the number
/// of occurrences of the byte it contains.</param>
/// <returns>The Huffman tree.</returns>
private BinaryTreeNode <byte> GetHuffmanTree(MinPriorityQueue <long, BinaryTreeNode <byte> > q)
{
while (q.Count > 1)
{
long p1 = q.MininumPriority;
BinaryTreeNode <byte> t1 = q.RemoveMinimumPriority();
long p2 = q.MininumPriority;
BinaryTreeNode <byte> t2 = q.RemoveMinimumPriority();
q.Add(new BinaryTreeNode <byte>(0, t1, t2), p1 + p2);
}
return(q.RemoveMinimumPriority());
}
/// <summary>
/// Finds a shortest path from the given start node to the given end node in the given graph.
/// </summary>
/// <param name="u">The start node.</param>
/// <param name="v">The end node.</param>
/// <param name="map">The graph.</param>
/// <param name="paths">The resulting shortest paths.</param>
/// <returns>The length of the shortest path.</returns>
private decimal ShortestPath(string u, string v, DirectedGraph <string, decimal> map,
out Dictionary <string, string> paths)
{
paths = new Dictionary <string, string>();
MinPriorityQueue <decimal, Tuple <string, string> > q = new MinPriorityQueue <decimal, Tuple <string, string> >();
paths.Add(u, u);
if (u == v)
{
return(0);
}
foreach (Tuple <string, decimal> t in map.OutgoingEdges(u))
{
string w = t.Item1;
decimal len = t.Item2;
q.Add(new Tuple <string, string>(u, w), len);
}
while (q.Count != 0)
{
decimal p = q.MininumPriority;
Tuple <string, string> edge = q.RemoveMinimumPriority();
string w = edge.Item1;
string x = edge.Item2;
if (!paths.ContainsKey(x))
{
paths.Add(x, w);
if (x == v)
{
return(p);
}
foreach (Tuple <string, decimal> t in map.OutgoingEdges(x))
{
string y = t.Item1;
decimal len = t.Item2;
q.Add(new Tuple <string, string>(x, y), p + len);
}
}
}
return(-1);
}
/// <summary>
/// Builds a HuffmanTree
/// </summary>
/// <param name="minQueue"></param>
/// <returns></returns>
private BinaryTreeNode <byte> HuffmanTree(MinPriorityQueue <long, BinaryTreeNode <byte> > minQueue)
{
while (minQueue.Count > 1)
{
long minimumOne = minQueue.MinimumPriority;
BinaryTreeNode <byte> minTreeOne = minQueue.RemoveMinimumPriority();
long minimumTwo = minQueue.MinimumPriority;
BinaryTreeNode <byte> minTreeTwo = minQueue.RemoveMinimumPriority();
minQueue.Add(minimumOne + minimumTwo, new BinaryTreeNode <byte>(0, minTreeOne, minTreeTwo));
}
return(minQueue.RemoveMinimumPriority());
}
/// <summary>
/// Gets a min-priority queue containing the leaves of a Huffman tree for the given frequency table.
/// The prioiries are the frequencies of the bytes contained in the leaves.
/// </summary>
/// <param name="freqTable">The frequency table.</param>
/// <returns>A min-priority queue containing the leaves of a Huffman tree.</returns>
private MinPriorityQueue <long, BinaryTreeNode <byte> > GetLeaves(long[] freqTable)
{
MinPriorityQueue <long, BinaryTreeNode <byte> > q = new MinPriorityQueue <long, BinaryTreeNode <byte> >();
for (int i = 0; i < 256; i++)
{
if (freqTable[i] > 0)
{
q.Add(new BinaryTreeNode <byte>((byte)i, null, null), freqTable[i]);
}
}
return(q);
}
/// <summary>
/// do not iterate with a byte
/// set priority to freq table equivalent
/// check zero, create node
/// </summary>
/// <param name=""></param>
/// <returns></returns>
private MinPriorityQueue <long, BinaryTreeNode <byte> > HuffBuild(long[] x)
{
x = freqTableBuilder(Console.ReadLine());
MinPriorityQueue <long, BinaryTreeNode <byte> > mpq = new
MinPriorityQueue <long, BinaryTreeNode <byte> >();
while (x.Length > mpq.Count)
{
BinaryTreeNode <byte> node = new BinaryTreeNode <byte>(Convert.ToByte(x), null, null);
mpq.Add(x[0], node);
}
return(mpq);
}
private BinaryTreeNode <byte> makeTree(MinPriorityQueue <long, BinaryTreeNode <byte> > min)
{
while (min.Count > 1)
{
long min1 = min.MininumPriority;
BinaryTreeNode <byte> temp1 = min.RemoveMinimumPriority();
long min2 = min.MininumPriority;
BinaryTreeNode <byte> temp2 = min.RemoveMinimumPriority();
BinaryTreeNode <byte> root = new BinaryTreeNode <byte>(0, temp1, temp2);
min.Add(root, (min1 + min2));
}
return(min.RemoveMinimumPriority());
}
/// <summary>
/// Builds the Huffman tree from the leaves.
/// </summary>
/// <param name="leaves"></param>
/// <returns></returns>
private BinaryTreeNode <byte> BuildTree(MinPriorityQueue <long, BinaryTreeNode <byte> > leaves)
{
while (leaves.Count > 1)
{
long priority1 = leaves.MinimumPriority;
BinaryTreeNode <byte> tree1 = leaves.RemoveMinimumPriority();
long priority2 = leaves.MinimumPriority;
BinaryTreeNode <byte> tree2 = leaves.RemoveMinimumPriority();
leaves.Add((priority1 + priority2), new BinaryTreeNode <byte>(0, tree1, tree2));
}
return(leaves.RemoveMinimumPriority());
}
/// <summary>
/// Uses Dijkstra's Algorithm to find the shortest distance in a graph between point u and v!
/// </summary>
/// <param name="u"> Name of the node we are starting at </param>
/// <param name="v">Name of the node that serves as our destination </param>
/// <param name="map"> Map that we are sifting through to find the shortest path </param>
/// <param name="paths"> Dictionary whose keys are a node, and the value is it's previous node </param>
/// <returns> The shortest path in decimal form! </returns>
private static decimal ShortestPath(string u, string v, DirectedGraph <string, decimal> map, out Dictionary <string, string> paths)
{
paths = new Dictionary <string, string>();
// String value in Edge is a node that has already been visited!
// Priority is the shortest path up until the source node (string value in Edge)
MinPriorityQueue <decimal, Edge <string, decimal> > queue = new MinPriorityQueue <decimal, Edge <string, decimal> >();
paths.Add(u, u);
if (u == v)
{
return(0);
}
foreach (Edge <string, decimal> edge in map.OutgoingEdges(u))
{
queue.Add(edge.Data, edge);
}
while (queue.Count != 0)
{
decimal minPriority = queue.MinimumPriority;
Edge <string, decimal> nextEdge = queue.RemoveMinimumPriority();
if (paths.ContainsKey(nextEdge.Destination) == false)
{
paths.Add(nextEdge.Destination, nextEdge.Source);
if (nextEdge.Destination == v)
{
return(minPriority);
}
foreach (Edge <string, decimal> edge in map.OutgoingEdges(nextEdge.Destination))
{
//queue.Add(edge.Data, edge);
queue.Add(minPriority + edge.Data, edge);
}
}
}
return(-1);
}
private MinPriorityQueue <long, BinaryTreeNode <byte> > makeLeaves(long[] size)
{
MinPriorityQueue <long, BinaryTreeNode <byte> > min = new MinPriorityQueue <long, BinaryTreeNode <byte> >();
for (int i = 0; i < size.Length; i++)
{
if (size[i] != 0)
{
BinaryTreeNode <byte> temp = new BinaryTreeNode <byte>((byte)i, null, null);
min.Add(temp, size[i]);
}
}
return(min);
}
/// <summary>
/// Builds the leaves of the Huffman tree.
/// </summary>
/// <param name="table"></param>
/// <returns></returns>
private MinPriorityQueue <long, BinaryTreeNode <byte> > BuildLeaves(long[] table)
{
MinPriorityQueue <long, BinaryTreeNode <byte> > leaves = new MinPriorityQueue <long, BinaryTreeNode <byte> >();
for (int i = 0; i < table.Length; i++)
{
if (table[i] != 0)
{
BinaryTreeNode <byte> temp = new BinaryTreeNode <byte>((byte)i, null, null);
leaves.Add(table[i], temp);
}
}
return(leaves);
}
} //END OF GerDifference METHOD
/// <summary>
/// Method used to find the highest frequencies of words in each file
/// </summary>
/// <param name="dictionary">Gives the number of occurrences of each word in each file</param>
/// <param name="numberOfWords">Gives the number of words in each file</param>
/// <param name="num">number of words to get</param>
/// <returns></returns>
public static MinPriorityQueue<float, WordFrequency> GetMostCommonWord(Dictionary<string, WordCount> dictionary, int[] numberOfWords, int number)
{
MinPriorityQueue<float, WordFrequency> queue = new MinPriorityQueue<float, WordFrequency>();
foreach (KeyValuePair<string, WordCount> pair in dictionary)
{
WordFrequency temp = new WordFrequency(pair.Value, numberOfWords);
queue.Add(temp[0] + temp[1], temp);
if (queue.Count > number)
{
queue.RemoveMinimumPriority();
} //END OF IF STATEMENT
} //END OF FOREACH LOOP
return queue;
} //END OF GetMostCommonWord METHOD
} //end ProcessFile
/// <summary>
/// This method removes the minimum priority object in the queue
/// </summary>
/// <param name="wordDictionary">This dictionary holds words and WordCounts</param>
/// <param name="wordCount">The count of words</param>
/// <param name="wordsToGet">The number of words to get</param>
/// <returns>Returns the frequencies in each file of the most common words</returns>
public static MinPriorityQueue <float, WordFrequency> GetMostCommonWords(Dictionary <string, WordCount> wordDictionary, int[] wordCount, int wordsToGet)
{
MinPriorityQueue <float, WordFrequency> minimumQueue = new MinPriorityQueue <float, WordFrequency>();
foreach (WordCount w in wordDictionary.Values)
{
WordFrequency frequency = new WordFrequency(w, wordCount);
minimumQueue.Add(frequency[0] + frequency[1], frequency);
if (minimumQueue.Count > wordsToGet)
{
minimumQueue.RemoveMinimumPriority();
} //end if
} // foreach
return(minimumQueue);
} // end GetMostCommonWords
/// <summary>
/// Creates a bunch of singleton tree nodes from the nonzero values in the array and adds them to
/// a Min Priority Queue
/// </summary>
/// <param name="bytes"> Array of long values being used </param>
/// <returns> Min Priority Queue full of singleton tree nodes</returns>
private static MinPriorityQueue <long, BinaryTreeNode <byte> > BuildLeaves(long[] bytes)
{
MinPriorityQueue <long, BinaryTreeNode <byte> > queue = new MinPriorityQueue <long, BinaryTreeNode <byte> >();
for (int i = 0; i < bytes.Length; i++)
{
if (bytes[i] != 0)
{
byte b = (byte)i;
BinaryTreeNode <byte> singleton = new BinaryTreeNode <byte>(b, null, null);
queue.Add(bytes[i], singleton);
}
}
return(queue);
}
/// <summary>
/// Constructs HuffmanTreeLeaves
/// </summary>
/// <param name="table"></param>
/// <returns></returns>
private MinPriorityQueue <long, BinaryTreeNode <byte> > HuffmanTreeLeaves(long[] table)
{
MinPriorityQueue <long, BinaryTreeNode <byte> > mPQ = new MinPriorityQueue <long, BinaryTreeNode <byte> >();
//MinPriorityQueue<Priority, Value>
for (int i = 0; i < table.Length; i++)
{
if (table[i] != 0)
{
BinaryTreeNode <byte> tempNode = new BinaryTreeNode <byte>((byte)i, null, null);
mPQ.Add(table[i], tempNode);
}
}
return(mPQ);
}
/// <summary>
/// returns a MinPriorityQueue whose elements contain the frequencies in each file of the most common words,
/// and whose priorities are the combined frequencies of each of these words
/// </summary>
/// <param name="dictionary">dictionary to take words from</param>
/// <param name="words">total number of words</param>
/// <param name="number">number of words needed to get</param>
/// <returns>min priority queue holding the frequencies</returns>
public static MinPriorityQueue <float, WordFrequency> GetMostCommonWords(Dictionary <string, WordCount> dictionary, int[] words, int number)
{
MinPriorityQueue <float, WordFrequency> queue = new MinPriorityQueue <float, WordFrequency>();
foreach (WordCount value in dictionary.Values)
{
WordFrequency wordFrequency = new WordFrequency(value, words);
queue.Add(wordFrequency[0] + wordFrequency[1], wordFrequency);
if (queue.Count > number)
{
queue.RemoveMinimumPriority();
}
}
return(queue);
}
/// <summary>
/// A method to get the words with highest combined frequencies
/// </summary>
/// <param name="d">A Dictionary<string, WordCount> giving the number of occurrences of each word in each file.</param>
/// <param name="numWords">An int[ ] of size 2 giving the number of words in each file.</param>
/// <param name="getNum">An int giving the number of words to get.</param>
/// <returns>a MinPriorityQueue<float, WordFrequency> whose elements contain the frequencies in each file of the most common words, and whose priorities are the combined frequencies of each of these words</returns>
public static MinPriorityQueue <float, WordFrequency> GetMostCommonWords(Dictionary <string, WordCount> d, int[] wordCount, int getNum)
{
MinPriorityQueue <float, WordFrequency> minQueue = new MinPriorityQueue <float, WordFrequency>();
foreach (WordCount w in d.Values)
{
WordFrequency freq = new WordFrequency(w, wordCount);
minQueue.Add(freq[0] + freq[1], freq);
if (minQueue.Count > getNum)
{
minQueue.RemoveMinimumPriority();
}
}
return(minQueue);
}
/// <summary>
/// Returns a MinPriorityQueue whose elements contain the frequencies in each file of the most common words.
/// </summary>
/// <param name="input">Dictionary containing a string and a WordCount object</param>
/// <param name="words">int array storing words</param>
/// <param name="num">int for comparing against count</param>
/// <returns></returns>
public static MinPriorityQueue <float, WordFrequency> GetMostCommonWord(Dictionary <string, WordCount> input, int[] words, int num)
{
MinPriorityQueue <float, WordFrequency> queue = new MinPriorityQueue <float, WordFrequency>();
foreach (KeyValuePair <string, WordCount> pair in input)
{
WordFrequency temp = new WordFrequency(pair.Value, words);
queue.Add(temp[0] + temp[1], temp);
if (queue.Count > num)
{
queue.RemoveMinimumPriority();
}
}
return(queue);
}
/// <summary>
/// Merges all of the singleton trees into a Huffman tree
/// </summary>
/// <param name="leaves"> Min Priority Queue containing all the singleton trees </param>
/// <returns> Returns the resulting Huffman Tree</returns>
private static BinaryTreeNode <byte> GetHuffmanTree(MinPriorityQueue <long, BinaryTreeNode <byte> > leaves)
{
while (leaves.Count > 1)
{
long p1 = leaves.MinimumPriority;
BinaryTreeNode <byte> firstRemoved = leaves.RemoveMinimumPriority();
long p2 = leaves.MinimumPriority;
BinaryTreeNode <byte> secondRemoved = leaves.RemoveMinimumPriority();
BinaryTreeNode <byte> newRoot = new BinaryTreeNode <byte>(0, firstRemoved, secondRemoved);
leaves.Add(p1 + p2, newRoot);
}
return(leaves.RemoveMinimumPriority());
}
/// <summary>
/// Builds the leaves of the Huffman tree
/// </summary>
/// <param name="longArray"></param>
/// <returns></returns>
private MinPriorityQueue <long, BinaryTreeNode <byte> > BuildHuffmanTreeLeaves(long[] ByteArray)
{
// Build a new Priority Queue
MinPriorityQueue <long, BinaryTreeNode <byte> > q = new MinPriorityQueue <long, BinaryTreeNode <byte> >();
for (int x = 0; x < ByteArray.Length; x++)
{
// Check if non-zero
if (ByteArray[x] != 0)
{
// Build new Tree Node with the indicated byte and add to the Byte Array
BinaryTreeNode <byte> newNode = new BinaryTreeNode <byte>((byte)x, null, null);
q.Add(newNode, ByteArray[x]);
}
}
return(q);
}
public void TestMSort()
{
int[] priorities = { 4, 2, 9, 7, 0, 8, 1, 3, 5, 6 };
string[] values = { "4", "2", "9", "7", "0", "8", "1", "3", "5", "6" };
MinPriorityQueue <int, string> pq = new MinPriorityQueue <int, string>();
for (int i = 0; i < priorities.Length; i++)
{
pq.Add(priorities[i], values[i]);
}
List <string> result = new List <string>();
while (pq.Count > 0)
{
result.Add(pq.RemoveMinimumPriority());
}
Assert.That(result, Is.Ordered.And.EquivalentTo(values));
}
/// <summary>
/// Builds the leaves of the Huffman tree
/// </summary>
/// <param name="longArray"></param>
/// <returns></returns>
private MinPriorityQueue<long, BinaryTreeNode<byte>> BuildHuffmanTreeLeaves(long[] ByteArray)
{
// Build a new Priority Queue
MinPriorityQueue<long, BinaryTreeNode<byte>> q = new MinPriorityQueue<long, BinaryTreeNode<byte>>();
for(int x = 0 ;x < ByteArray.Length;x++)
{
// Check if non-zero
if(ByteArray[x] != 0)
{
// Build new Tree Node with the indicated byte and add to the Byte Array
BinaryTreeNode<byte> newNode = new BinaryTreeNode<byte>((byte)x,null, null);
q.Add(newNode, ByteArray[x]);
}
}
return q;
}
/// <summary>
/// Build huffman tree from given priority queue
/// </summary>
/// <param name="q"></param>
/// <returns></returns>
private BinaryTreeNode<byte> BuildHuffmanTree(MinPriorityQueue<long,BinaryTreeNode<byte>> q)
{
while(q.Count>1)
{
// Get and remove the two smallest priorities and their associated trees
long temp1 = q.MininumPriority;
BinaryTreeNode<byte> tree1 = q.RemoveMinimumPriority();
long temp2 = q.MininumPriority;
BinaryTreeNode<byte> tree2 = q.RemoveMinimumPriority();
// Construct a new binary tree with these trees as its children and 0 as its data (which will be unused).
BinaryTreeNode<byte> newBinTree = new BinaryTreeNode<byte>(0,tree1,tree2);
// Add the resulting tree to the min-priority queue with a priority equal to the sum of the priorities of its children.
q.Add(newBinTree, temp1+temp2);
}
return q.RemoveMinimumPriority();
}
