///// <summary>Gets a copy of sorted Similars without elements with undefined number.</summary>
///// <returns>The sorted Similars without elements with undefined number</returns>
//public Similars GetShrink()
//{
// int i;
// Array.Sort(_numbers);
// for (i = 0; i < Count; i++)
// if (this[i] == UndefNumber)
// break;
// Similars res = new Similars(i);
// Array.Copy(_numbers, res._numbers, i);
// return res;
//}
/// <summary>Returns the Coefficient of Variation.</summary>
/// <param name="startIndex">The index in the input sequence at which scanning begins.</param>
/// <param name="length">The length of scanning range.</param>
/// <param name="seedNumber">The serial number of seed word.</param>
/// <returns>Coefficient of Variation</returns>
/// <remarks>This instance should be shrinked.</remarks>
public float GetCV(int startIndex, int length, int seedNumber)
{
if (Count == 0)
{
return(0);
}
int i, j = 0, number, lastFound = -1;
int stopInd = startIndex + length - Words.WordLength;
// set the array of count of neighbouring word's (clusters) with max possible capacity
int[] grps = new int[length];
int k = 1;
for (i = startIndex; i < stopInd; i++)
{
number = Words.GetNumber(Sequence.Original, i);
// this collection is sorted by increasing!
if (number != seedNumber &&
Array.BinarySearch(_numbers, number) < 0) // word is not belong to similars
{
continue;
}
if (lastFound >= 0) // count began
{
if (i - lastFound <= _DepthOfClastering) // founded word is in group
{
k++; // increase group counter
}
else // founded word is out of group
{
grps[j++] = k; // close current group
k = 1; // start new group
}
}
lastFound = i; // remember current position
}
// fill sum Counter
Average.SumCounter counter = new Average.SumCounter();
// check i<cnt needs when groups is full, in other words, when each "group" has just one member
for (i = 0; i < Count && (k = grps[i]) > 0; i++)
{
counter += k;
}
return(new Average(counter).CV);
}
/// <summary>Creates and filled a shrinked or 'crude' instance of Patterns class from the range of the inputArray array
/// and calculate their averages and standart deviation values.
/// </summary>
/// <param name="worker">The BackgroundWorker in wich Processing is run.</param>
/// <param name="startIndex">The index in the input sequence at which scanning begins.</param>
/// <param name="length">The length of scanning range.</param>
/// <param name="shakeCnt">The amount of shakes.</param>
/// <param name="avrgs">Null in case of Individual mode; the array of single Average otherwise.</param>
/// <param name="maxFreqNumber">The number of Pattern with max Frequence: used in 'Global' only.</param>
/// <param name="stepCntOnShake">The number of progress bar steps generated by method within one shake; 0 if without progress bar steps.</param>
/// <param name="isDrawPlot">True if a plot should be drawing; otherwise, false.</param>
/// <returns>Sorted by Frequence and shrinked collection in case of isSortByFreq=true; otherwise sorted by Number and unshrinked.</returns>
public static Patterns GetTreatedPatterns(
BackgroundWorker worker,
int startIndex, int length, short shakeCnt,
ref Average[] avrgs, ref int maxFreqNumber, float stepCntOnShake,
bool isDrawPlot)
{
int strictLength = length - Words.WordLength;
int[] strictFreqs = new int[Words.Count];
int loopsPerStep = stepCntOnShake > 0 ? (int)(Words.Count / stepCntOnShake) : -1;
Patterns mainPtns = new Patterns();
mainPtns.Init(
worker, Sequence.Original, startIndex,
strictLength, strictFreqs, loopsPerStep, ref maxFreqNumber, true, isDrawPlot
);
if (shakeCnt > 0) // calculate mean & SD
{
int i;
int maxFreqNumberTmp = 0;
Patterns shakedPtns = new Patterns();
// corretcing ProgressBar steps for for shake and scanning
int shakeSteps = 0;
//if (loopsPerStep > 3) shakeSteps = 3;
//else if (loopsPerStep > 2) shakeSteps = 2;
//else if (loopsPerStep > 1) shakeSteps = 1;
loopsPerStep -= shakeSteps;
if (avrgs != null) //*** Max Average Choice mode set
{
Average.SumCounter sumCounter = new Average.SumCounter();
// search patterns with max Frequance for each shake and add this value to the sumCounter
for (i = 0; i < shakeCnt; i++)
{
// we need only max Frequance from the shaked Patterns
sumCounter += shakedPtns.Init(worker,
Sequence.Shake(startIndex, length, worker, shakeSteps),
0, strictLength, strictFreqs, loopsPerStep, ref maxFreqNumberTmp, false, isDrawPlot
);
}
avrgs[0] = new Average(sumCounter); // set total Average on the first place;
}
else //*** Individual Average Choice mode set
{
// this case is possible only in Local task, so mainPtns is always sorted and shrinked
// create and fill the array of sum counters of frequencies from shaked Patterns;
// it is 'sinchronised' with shakedPtns, or the same order as a shakedPtns
Average.SumCounter[] SCounters = new Average.SumCounter[Words.Count];
maxFreqNumberTmp = -1; // disable max frequency return
for (int j = 0; j < shakeCnt; j++)
{
shakedPtns.Init(worker,
Sequence.Shake(startIndex, length, worker, shakeSteps),
0, strictLength, strictFreqs, loopsPerStep, ref maxFreqNumberTmp, false, isDrawPlot
);
for (i = 0; i < Words.Count; i++)
{
//if (shakedPtns[i].Freq > 0)
// SCounters[i] += shakedPtns[i].Freq;
if (shakedPtns[i] > 0)
{
SCounters[i] += shakedPtns[i];
}
}
}
// set the average of frequency and SD for each Pattern in the initial collection
avrgs = new Average[mainPtns.Count];
for (i = 0; i < mainPtns.Count; i++) // each initial pattern with unzero Frequency...
{
avrgs[i] = new Average(SCounters[i]);
}
}
}
return(mainPtns);
}
