/// <summary>
/// An estimated characteristic of occurrence of the subject word in the sequence
/// </summary>
/// <param name="accord">
/// Checking word.
/// </param>
/// <param name="chainLength">
/// Length of whole sequence.
/// </param>
/// <param name="winLen">
/// Length of the scanning window.
/// </param>
/// <param name="minusOne">
/// Data for "minus one" subword.
/// </param>
/// <param name="mid">
/// Data for "minus two" subword.
/// </param>
/// <returns>
/// Design characteristic of occurrence of the word.
/// </returns>
public double DesignExpected(List<string> accord, int chainLength, int winLen, DataCollector minusOne, DataCollector mid)
{
int shortWord = 2;
int midlLength = winLen - 2;
int minusLength = winLen - 1;
List<int> left = minusOne.Positions(accord.GetRange(0, accord.Count - 1));
List<int> right = minusOne.Positions(accord.GetRange(1, accord.Count - 1));
List<int> middle = midlLength != 0 ? mid.Positions(accord.GetRange(1, accord.Count - 2)) : new List<int>();
double criteria = -1;
if (winLen == shortWord)
{
criteria = Frequency(left, chainLength, minusLength)
* Frequency(right, chainLength, minusLength);
}
else if (middle != null)
{
criteria = (Frequency(left, chainLength, minusLength)
* Frequency(right, chainLength, minusLength))
/ Frequency(middle, chainLength, midlLength);
}
return criteria;
}
/// <summary>
/// The find.
/// </summary>
/// <param name="par">
/// The par.
/// </param>
/// <returns>
/// The <see cref="T:KeyValuePair{List{string},List{int}}?"/>.
/// </returns>
public override sealed KeyValuePair<List<string>, List<int>>? Find(ContentValues par)
{
var convoluted = (ComplexChain)par.Get(Enum.GetName(typeof(Formalism), Formalism.Sequence));
double pbalance = (int)par.Get(Enum.GetName(typeof(Parameter), Parameter.Balance)) / 100.0;
int windowLen = (int)par.Get(Enum.GetName(typeof(Parameter), Parameter.Window));
var alphabet = (FrequencyDictionary)par.Get(Enum.GetName(typeof(Formalism), Formalism.Alphabet));
var level = (double)par.Get(Enum.GetName(typeof(Parameter), Parameter.CurrentThreshold));
int scanStep = 1;
int disp = 0;
int length = convoluted.GetLength();
fullEntry = new DataCollector();
minusOneEntry = new DataCollector();
minusTwoEntry = new DataCollector();
var it = new StartIterator(convoluted, windowLen, scanStep);
CriterionMethod criteriaCalculator = new ConvolutedCriterionMethod();
while (it.HasNext())
{
it.Next();
fullEntry.Add(it, disp);
FindLess(it);
}
CalculateStd(convoluted, pbalance, windowLen, length, criteriaCalculator);
return DiscardCompositeWords(alphabet, level);
}
