C# 哈夫曼树：穿越
我不知道我将如何攻击哈夫曼树的遍历。这棵树是正确的，我只是很难想出如何以一种好的方式穿过它。由于某种原因，我的遍历方法没有给出任何结果 更新：清理了代码，使其更加面向对象 节点类：C# 哈夫曼树：穿越,c#,recursion,traversal,huffman-code,C#,Recursion,Traversal,Huffman Code,我不知道我将如何攻击哈夫曼树的遍历。这棵树是正确的，我只是很难想出如何以一种好的方式穿过它。由于某种原因，我的遍历方法没有给出任何结果 更新：清理了代码，使其更加面向对象 节点类： public class Node { public int frekvens; //Frequency public char tegn; //Symbol public Node venstre; //Left child public Node høyre; //Right ch
public class Node
{
public int frekvens; //Frequency
public char tegn; //Symbol
public Node venstre; //Left child
public Node høyre; //Right child
public string s; //result string
public string resultat;
public Node (char c) // Node constructor containing symbol.
{
frekvens = 1;
tegn = c;
}
public Node (int f, Node venstre, Node høyre) // Node Constructor containing frequency and children
{
frekvens = f;
this.venstre = venstre;
this.høyre = høyre;
}
public Node (Node node) // Node constructor containing a node
{
frekvens = node.frekvens;
tegn = node.tegn;
this.venstre = venstre;
this.høyre = høyre;
}
public void ØkMed1() // Inkrement frequency by one
{
frekvens = frekvens + 1;
}
public char getVenstreTegn ()
{
return venstre.tegn;
}
public char getHøyreTegn ()
{
return venstre.tegn;
}
public int getVenstreFrekvens ()
{
return venstre.frekvens;
}
public int getHøyreFrekvens ()
{
return høyre.frekvens;
}
public int getFrekvens()
{
return frekvens;
}
public bool ErTegn(char c)
{
if ( c == tegn)
{
return false;
}
else
{
return true;
}
}
//Pretty sure this does not work as intended
public string traverser (Node n) //Traverse the tree
{
if (n.tegn != '\0') //If the node containes a symbol --> a leaf
{
resultat += s;
}
else
{
if (n.getVenstreTegn() == '\0') //If left child does not have a symbol
{
s += "0";
traverser(n.venstre);
}
if (n.getHøyreTegn() == '\0') //If right child does not have a symbol
{
s += "1";
traverser(n.høyre);
}
}
return resultat;
}
public string Resultat() //Used priviously to check if i got the correct huffman tree
{
string resultat;
resultat = "Tegn: " + Convert.ToString(tegn) +" frekvens: " + Convert.ToString(frekvens) + "\n";
return resultat;
}
}
public class Huffman_Tre
{
string treString;
List<Node> noder = new List<Node>();
public Node rot;
public void bygg (string input)
{
bool funnet; //Found
char karakter; //character
for (int i = 0; i < input.Length;i++) //Loops through string and sets character
//with coresponding freqeuncy in the node list
{
karakter = input[i];
funnet = false; //default
for (int j = 0; j< noder.Count; j++)
{
if (noder[j].ErTegn(karakter) == false) //if the character already exists
{
noder[j].ØkMed1(); //inkrement frequency by one
funnet = true;
break;
}
}
if (!funnet) //if the character does not exist
{
noder.Add(new Node(karakter)); //add the character to list
}
}
//Sorting node list acending by frequency
var sortertListe = noder.OrderBy(c => c.frekvens).ToList();
noder = sortertListe;
do
{
noder.Add(new Node((noder[0].frekvens + noder[1].frekvens), noder[0],noder[1]));
//Remove the leaf nodes
noder.RemoveAt(0);
noder.RemoveAt(0);
} while(noder.Count >= 2);
}
public Node getRot()
{
return rot;
}
public string visTre()
{
foreach (Node node in noder)
{
treString += node.Resultat();
}
return treString;
}
public bool erNull()
{
if (noder[0].tegn == '\0')
{
return true;
}
else
return false;
}
}
由于我还有一点时间，我在玩C 6.0的时候制作了一个哈夫曼树的例子。它还没有优化，甚至到目前为止都没有！，但作为一个例子，它可以很好地工作。这将有助于你找到你的“挑战”可能出现的地方。由于我的英语远远好于我的斯堪的纳维亚知识，我用英语命名，希望你不要介意 首先，让我们从保持频率的类开始
public sealed class HuffmanFrequencyTable
{
#region Properties
/// <summary>
/// Holds the characters and their corresponding frequencies
/// </summary>
public Dictionary<char, int> FrequencyTable { get; set; } = new Dictionary<char, int>();
#endregion
#region Methods
/// <summary>
/// Clears the internal frequency table
/// </summary>
public void Clear()
{
FrequencyTable?.Clear();
}
/// <summary>
/// Accepts and parses a new line (string) which is then
/// merged with the existing dictionary or frequency table
/// </summary>
/// <param name="line">The line to parse</param>
public void Accept(string line)
{
if (!string.IsNullOrEmpty(line))
{
line.GroupBy(ch => ch).
ToDictionary(g => g.Key, g => g.Count()).
ToList().
ForEach(x => FrequencyTable[x.Key] = x.Value);
}
}
/// <summary>
/// Performs a dump of the frequency table, ordering all characters, lowest frequency first.
/// </summary>
/// <returns>The frequency table in the format 'character [frequency]'</returns>
public override string ToString()
{
return FrequencyTable?.PrintFrequencies();
}
#endregion
}
string input = tbInput.Text;
Tree.BuildTree(input); //Build the huffman tree
BitArray encoded = Tree.Encode(input); //Encode the tree
//First show the generated binary output
tbBinaryOutput.Text = string.Join(string.Empty, encoded.Cast<bool>().Select(bit => bit ? "1" : "0"));
//Next, convert the binary output to the new characterized output string.
byte[] bytes = new byte[(encoded.Length / 8) + 1];
encoded.CopyTo(bytes, 0);
tbOutput.Text = Encoding.Default.GetString(bytes); //Write the compressed output to the textbox.
//First convert the compressed output to a bit array again again and skip trailing bits.
bool[] boolAr = new BitArray(Encoding.Default.GetBytes(tbOutput.Text)).Cast<bool>().Take(Tree.BitCountForTree).ToArray();
BitArray encoded = new BitArray( boolAr );
string decoded = Tree.Decode(encoded);
MessageBox.Show(decoded, "Decoded result: ", MessageBoxButtons.OK, MessageBoxIcon.Information);
string input = tbInput.Text;
Tree.BuildTree(input); //Build the huffman tree
BitArray encoded = Tree.Encode(input); //Encode the tree
//First show the generated binary output
tbBinaryOutput.Text = string.Join(string.Empty, encoded.Cast<bool>().Select(bit => bit ? "1" : "0"));
//Next, convert the binary output to the new characterized output string.
byte[] bytes = new byte[(encoded.Length / 8) + 1];
encoded.CopyTo(bytes, 0);
tbOutput.Text = Encoding.Default.GetString(bytes); //Write the compressed output to the textbox.
string input = tbInput.Text;
Tree.BuildTree(input); //Build the huffman tree
BitArray encoded = Tree.Encode(input); //Encode the tree
//First show the generated binary output
tbBinaryOutput.Text = string.Join(string.Empty, encoded.Cast<bool>().Select(bit => bit ? "1" : "0"));
//Next, convert the binary output to the new characterized output string.
byte[] bytes = new byte[(encoded.Length / 8) + 1];
encoded.CopyTo(bytes, 0);
tbOutput.Text = Encoding.Default.GetString(bytes); //Write the compressed output to the textbox.
<>现在这个代码可以使用一些优化，因为你可以考虑使用数组而不是字典。还有更多，但这取决于您的考虑。因为我还有一点时间，所以在玩C 6.0时，我制作了一个哈夫曼树的示例。它还没有优化，甚至到目前为止都没有！，但作为一个例子，它可以很好地工作。这将有助于你找到你的“挑战”可能出现的地方。由于我的英语远远好于我的斯堪的纳维亚知识，我用英语命名，希望你不要介意 首先，让我们从保持频率的类开始
public sealed class HuffmanFrequencyTable
{
#region Properties
/// <summary>
/// Holds the characters and their corresponding frequencies
/// </summary>
public Dictionary<char, int> FrequencyTable { get; set; } = new Dictionary<char, int>();
#endregion
#region Methods
/// <summary>
/// Clears the internal frequency table
/// </summary>
public void Clear()
{
FrequencyTable?.Clear();
}
/// <summary>
/// Accepts and parses a new line (string) which is then
/// merged with the existing dictionary or frequency table
/// </summary>
/// <param name="line">The line to parse</param>
public void Accept(string line)
{
if (!string.IsNullOrEmpty(line))
{
line.GroupBy(ch => ch).
ToDictionary(g => g.Key, g => g.Count()).
ToList().
ForEach(x => FrequencyTable[x.Key] = x.Value);
}
}
/// <summary>
/// Performs a dump of the frequency table, ordering all characters, lowest frequency first.
/// </summary>
/// <returns>The frequency table in the format 'character [frequency]'</returns>
public override string ToString()
{
return FrequencyTable?.PrintFrequencies();
}
#endregion
}
string input = tbInput.Text;
Tree.BuildTree(input); //Build the huffman tree
BitArray encoded = Tree.Encode(input); //Encode the tree
//First show the generated binary output
tbBinaryOutput.Text = string.Join(string.Empty, encoded.Cast<bool>().Select(bit => bit ? "1" : "0"));
//Next, convert the binary output to the new characterized output string.
byte[] bytes = new byte[(encoded.Length / 8) + 1];
encoded.CopyTo(bytes, 0);
tbOutput.Text = Encoding.Default.GetString(bytes); //Write the compressed output to the textbox.
//First convert the compressed output to a bit array again again and skip trailing bits.
bool[] boolAr = new BitArray(Encoding.Default.GetBytes(tbOutput.Text)).Cast<bool>().Take(Tree.BitCountForTree).ToArray();
BitArray encoded = new BitArray( boolAr );
string decoded = Tree.Decode(encoded);
MessageBox.Show(decoded, "Decoded result: ", MessageBoxButtons.OK, MessageBoxIcon.Information);
string input = tbInput.Text;
Tree.BuildTree(input); //Build the huffman tree
BitArray encoded = Tree.Encode(input); //Encode the tree
//First show the generated binary output
tbBinaryOutput.Text = string.Join(string.Empty, encoded.Cast<bool>().Select(bit => bit ? "1" : "0"));
//Next, convert the binary output to the new characterized output string.
byte[] bytes = new byte[(encoded.Length / 8) + 1];
encoded.CopyTo(bytes, 0);
tbOutput.Text = Encoding.Default.GetString(bytes); //Write the compressed output to the textbox.
string input = tbInput.Text;
Tree.BuildTree(input); //Build the huffman tree
BitArray encoded = Tree.Encode(input); //Encode the tree
//First show the generated binary output
tbBinaryOutput.Text = string.Join(string.Empty, encoded.Cast<bool>().Select(bit => bit ? "1" : "0"));
//Next, convert the binary output to the new characterized output string.
byte[] bytes = new byte[(encoded.Length / 8) + 1];
encoded.CopyTo(bytes, 0);
tbOutput.Text = Encoding.Default.GetString(bytes); //Write the compressed output to the textbox.
还有更多，但这取决于您的考虑。Sindre，也许首先使用二叉树更方便。正如哈夫曼的算法将根据字符的频率或形成根的频率总和来确定二进制数字1或0。如果你还需要更多的提示，我忽略了你已经在使用二叉树的事实。我道歉。尽管如此，它还是促使我建立了一个带有遍历的哈夫曼算法。当然，我已经在我的答案中发布了它。顺便说一下，您的遍历不起作用，因为您实际上没有遍历树的左右节点。感谢您的回复，在我昨天收到gmail之前，我以为这个帖子已经死了：我写的代码写得太快了。在高中学习c一个月后，当我现在看到它的时候，它不是很好。我将很快重新制作这个应用程序，使它完全工作。这个哈夫曼编码的算法非常简洁，也许首先使用二叉树会更方便。正如哈夫曼的算法将根据字符的频率或形成根的频率总和来确定二进制数字1或0。如果你还需要更多的提示，我忽略了你已经在使用二叉树的事实。我道歉。尽管如此，它还是促使我建立了一个带有遍历的哈夫曼算法。当然，我已经在我的答案中发布了它。顺便说一下，您的遍历不起作用，因为您实际上没有遍历树的左右节点。感谢您的回复，在我昨天收到gmail之前，我以为这个帖子已经死了：我写的代码写得太快了。在高中学习c一个月后，当我现在看到它的时候，它不是很好。我将很快重新制作这个应用程序，使它完全工作。这是一个相当简洁的算法，这个哈夫曼代码回答得很好！随着我编程语言知识的提高，我越来越尊重好的代码。我将尽量不看你的代码太多，而是阅读你的帮助说明，因为我确实希望从头开始创建这个应用程序。现在应该容易多了：D这是一个非常有趣的程序，我希望你在写的时候也能有一些乐趣；我真的做到了，别担心：-。我很高兴它有帮助！回答得好！随着我编程语言知识的提高，我越来越尊重好的代码。我将尽量不看你的代码太多，而是阅读你的帮助说明，因为我确实希望从头开始创建这个应用程序。现在应该容易多了：D这是一个非常有趣的程序，我希望你在写的时候也能有一些乐趣；我真的做到了，别担心：-。我很高兴它有帮助！