//This function generate statistic data to summarizations in extended form.
//It checks dependences beetwen duarion and dynamic of change, and also beetwen variability and dynamic of change.
public List<SummaryRating> extendedFormDagrees(TrendsStatistics[] trendsStatistics, SummarizationParameters sumParams)
{
TrendsStatistics changeStatistics = new TrendsStatistics();
ImprecisionDegree imp = new ImprecisionDegree();
double characteristic = 0;
SummaryRating extendedSummary = new SummaryRating();
double[] dynamicOfChangeSum = new double[trendsStatistics[0].dynamicOfChangeData.Length];
//here we will gather all characteristics with their dagrees
List<SummaryRating> extendedSummaryRating = new List<SummaryRating>();
//dagree of focus
for (int i = 0; i < trendsStatistics.Length; i++)
{
changeStatistics.addStatisticValues(changeStatistics, trendsStatistics[i]);
}
for (int c = 0; c < trendsStatistics[0].dynamicOfChangeData.Length; c++)
{
dynamicOfChangeSum[c] = changeStatistics.dynamicOfChangeData[c].value;
}
//dagree of imprecision
imp = calculateImprecision(sumParams);
//dagree of truth: dynamic of change and duration
for (int c = 0; c < trendsStatistics[0].dynamicOfChangeData.Length; c++)
{
for (int d = 0; d < trendsStatistics[0].durationData.Length; d++)
{
for (int i = 0; i < trendsStatistics.Length; i++)
{
characteristic += (trendsStatistics[i].durationData[d].value < trendsStatistics[i].dynamicOfChangeData[c].value)
? trendsStatistics[i].durationData[d].value : trendsStatistics[i].dynamicOfChangeData[c].value;
}
extendedSummary.type = 2;
extendedSummary.P = trendsStatistics[0].durationData[d].name;
extendedSummary.R = trendsStatistics[0].dynamicOfChangeData[c].name;
extendedSummary.truthCoefficient = characteristic / dynamicOfChangeSum[c];
extendedSummary.focusDagree = dynamicOfChangeSum[c] / trendsStatistics.Length;
extendedSummary.imprecisionDegree = 0.5 * imp.durationImprecision + 0.5 * imp.dynamicOfChangeImprecision;
extendedSummaryRating.Add(extendedSummary);
extendedSummary = new SummaryRating();
characteristic = 0;
}
}
//dagree of truth: dynamic of change and variability
for (int c = 0; c < trendsStatistics[0].dynamicOfChangeData.Length; c++)
{
for (int v = 0; v < trendsStatistics[0].variabilityData.Length; v++)
{
for (int i = 0; i < trendsStatistics.Length; i++)
{
characteristic += (trendsStatistics[i].variabilityData[v].value < trendsStatistics[i].dynamicOfChangeData[c].value)
? trendsStatistics[i].variabilityData[v].value : trendsStatistics[i].dynamicOfChangeData[c].value;
}
extendedSummary.type = 2;
extendedSummary.P = trendsStatistics[0].variabilityData[v].name;
extendedSummary.R = trendsStatistics[0].dynamicOfChangeData[c].name;
extendedSummary.truthCoefficient = characteristic / dynamicOfChangeSum[c];
extendedSummary.focusDagree = dynamicOfChangeSum[c] / trendsStatistics.Length;
extendedSummary.imprecisionDegree = 0.5 * imp.variabilityImprecision + 0.5 * imp.dynamicOfChangeImprecision;
extendedSummaryRating.Add(extendedSummary);
extendedSummary = new SummaryRating();
characteristic = 0;
}
}
return extendedSummaryRating;
}
//Here we gather all data about trends and make statistics, wchich tell us for example how many (in fuzzy value -> [0,1]) trends are quickly increasing
public List<SummaryRating> shortFormDegrees(TrendsStatistics[] trendsStatistics, SummarizationParameters sumParams)
{
List<SummaryRating> shortSummaryRating = new List<SummaryRating>();
SummaryRating shortSummary = new SummaryRating();
TrendsStatistics sumStatistics = new TrendsStatistics();
ImprecisionDegree imp = new ImprecisionDegree();
int numberOfTrends = trendsStatistics.Length;
//dagree of imprecision
imp = calculateImprecision(sumParams);
for (int i = 0; i < trendsStatistics.Length; i++)
{
sumStatistics.addStatisticValues(sumStatistics, trendsStatistics[i]);
}
for (int i = 0; i < sumStatistics.dynamicOfChangeData.Length; i++)
{
shortSummary.type = 1;
shortSummary.P = trendsStatistics[0].dynamicOfChangeData[i].name;
shortSummary.truthCoefficient = sumStatistics.dynamicOfChangeData[i].value / numberOfTrends;
shortSummary.imprecisionDegree = imp.dynamicOfChangeImprecision;
shortSummaryRating.Add(shortSummary);
shortSummary = new SummaryRating();
}
for (int i = 0; i < sumStatistics.durationData.Length; i++)
{
shortSummary.type = 1;
shortSummary.P = trendsStatistics[0].durationData[i].name;
shortSummary.truthCoefficient = sumStatistics.durationData[i].value / numberOfTrends;
shortSummary.imprecisionDegree = imp.durationImprecision;
shortSummaryRating.Add(shortSummary);
shortSummary = new SummaryRating();
}
for (int i = 0; i < sumStatistics.variabilityData.Length; i++)
{
shortSummary.type = 1;
shortSummary.P = trendsStatistics[0].variabilityData[i].name;
shortSummary.truthCoefficient = sumStatistics.variabilityData[i].value / numberOfTrends;
shortSummary.imprecisionDegree = imp.variabilityImprecision;
shortSummaryRating.Add(shortSummary);
shortSummary = new SummaryRating();
}
return shortSummaryRating;
}