public override bool Equals(System.Object obj)
{
// If parameter is null return false.
if (obj == null)
{
return(false);
}
// If parameter cannot be cast to Point return false.
MarkovWord p = obj as MarkovWord;
if ((System.Object)p == null)
{
return(false);
}
// Return true if the fields match:
return((Text == p.Text) && (POS == p.POS));
}
private void AnalyzeButton_Click(object sender, EventArgs e)
{
Dictionary <MarkovKey, Dictionary <MarkovWord, int> > wordDict = new Dictionary <MarkovKey, Dictionary <MarkovWord, int> >(new MarkovKeyEqualityComparer());
int wordOrder = 2;
wordDict = BuildWordDict(InputBox.Text, wordOrder);
wordDict = BuildWordDict(InputBox2.Text, wordDict, wordOrder);
int outputLength = 1000;
StringBuilder chain = new StringBuilder("");
System.Random r = new System.Random();
// string currentWords[] = new string[]{ "In", "a" };
Queue <MarkovWord> currentWords = new Queue <MarkovWord>();
for (int i = 0; i < wordOrder; i++)
{
currentWords.Enqueue(wordDict.ElementAt(0).Key.Words.ElementAt(i));
}
for (int i = 0; i < outputLength; i++)
{
MarkovWord dequeuedItem = currentWords.Dequeue();
chain.Append(dequeuedItem.Text + " ");
MarkovKey newKey = new MarkovKey(new List <MarkovWord>());
newKey.Words.Add(dequeuedItem);
for (int j = 0; j < wordOrder - 1; j++)
{
newKey.Words.Add(currentWords.ElementAt(j));
}
currentWords.Enqueue(RetrieveRandomWord(wordDict[newKey], r));
}
OutputBox.Text = chain.ToString();
//Stanford.NLP.CoreNLP.CSharp.TaggerDemo.TagText(InputBox.Text);
}
public bool Equals(MarkovWord x)
{
return((x.Text == Text) && (x.POS == POS));
}