public static void TestEdit()
{
string w1 = Console.ReadLine();
string w2 = Console.ReadLine();
double d = EditDistance.ComputeEditDistanceDP(w1, w2);
Console.WriteLine(w1 + " , " + w2 + " : " + d);
}
public static void PrintEditDistance(List <Tuple <double, string> > values, List <Tuple <double, string> > edList, string word)
{
pos = new Tuple <int, int>(Console.CursorLeft, Console.CursorTop);
SetCursor(0, 2);
ClearLine();
Console.Write("Edit Distance: ");
for (int i = 0; i < promptCount && i < values.Count; i++)
{
Console.Write(String.Format("{2}){0}: {1:0.00} ", values[i].Item2, EditDistance.ComputeEditDistanceDP(values[i].Item2, word), (i + 1) % 10));
}
SetCursor(pos.Item1, pos.Item2);
}
public static List <Tuple <double, string> > EvaluateLikelihood(Queue <string> predicate, string currentWord, Model m)
{
model = m;
List <Tuple <double, string> > values = new List <Tuple <double, string> >();
dictionary = model.GetDictionary();
ed = EditDistance.ComputeEditDistances(dictionary, currentWord);
SetUpDistributionVector(predicate);
foreach (Tuple <double, string> t in ed)
{
double value = ComputeWeightedProbability(t.Item2);
value /= (t.Item1 * edWeight);
value *= scale;
values.Add(new Tuple <double, string>(value, t.Item2));
}
values.Sort();
values.Reverse();
Writer.PrintPostWriteEvaluation(values);
Writer.PrintProbabilityDistribution(values, distributions[0]);
Writer.PrintEditDistance(values, ed, currentWord);
return(values);
}
