protected HeatMap(HeatMap original, Cloner cloner)
: base(original, cloner)
{
this.title = original.title;
this.minimum = original.minimum;
this.maximum = original.maximum;
}
public override IOperation Apply()
{
int updateInterval = UpdateIntervalParameter.Value.Value;
IntValue updateCounter = UpdateCounterParameter.ActualValue;
// if counter does not yet exist then initialize it with update interval
// to make sure the solutions are analyzed on the first application of this operator
if (updateCounter == null)
{
updateCounter = new IntValue(updateInterval);
UpdateCounterParameter.ActualValue = updateCounter;
}
//analyze solutions only every 'updateInterval' times
if (updateCounter.Value != updateInterval)
{
updateCounter.Value++;
return(base.Apply());
}
updateCounter.Value = 1;
bool storeHistory = StoreHistoryParameter.Value.Value;
int count = CurrentScopeParameter.ActualValue.SubScopes.Count;
if (count > 1)
{
var similarityCalculator = SimilarityCalculatorParameter.Value;
// calculate solution similarities
var similarityMatrix = similarityCalculator.CalculateSolutionCrowdSimilarity(CurrentScopeParameter.ActualValue);
double[,] similarities = new double[similarityMatrix.Length, similarityMatrix[0].Length];
for (int i = 0; i < similarityMatrix.Length; i++)
{
for (int j = 0; j < similarityMatrix[0].Length; j++)
{
similarities[i, j] = similarityMatrix[i][j];
}
}
// calculate minimum, average and maximum similarities
double similarity;
double[] minSimilarities = new double[count];
double[] avgSimilarities = new double[count];
double[] maxSimilarities = new double[count];
for (int i = 0; i < count; i++)
{
minSimilarities[i] = 1;
avgSimilarities[i] = 0;
maxSimilarities[i] = 0;
for (int j = 0; j < count; j++)
{
if (i != j)
{
similarity = similarities[i, j];
if ((similarity < 0) || (similarity > 1))
{
throw new InvalidOperationException("Solution similarities have to be in the interval [0;1].");
}
if (minSimilarities[i] > similarity)
{
minSimilarities[i] = similarity;
}
avgSimilarities[i] += similarity;
if (maxSimilarities[i] < similarity)
{
maxSimilarities[i] = similarity;
}
}
}
avgSimilarities[i] = avgSimilarities[i] / (count - 1);
}
double avgMinSimilarity = minSimilarities.Average();
double avgAvgSimilarity = avgSimilarities.Average();
double avgMaxSimilarity = maxSimilarities.Average();
// fetch results collection
ResultCollection results;
if (!ResultsParameter.ActualValue.ContainsKey(DiversityResultName))
{
results = new ResultCollection();
ResultsParameter.ActualValue.Add(new Result(DiversityResultName, results));
}
else
{
results = (ResultCollection)ResultsParameter.ActualValue[DiversityResultName].Value;
}
// store similarities
HeatMap similaritiesHeatMap = new HeatMap(similarities, "Solution Similarities", 0.0, 1.0);
if (!results.ContainsKey("Solution Similarities"))
{
results.Add(new Result("Solution Similarities", similaritiesHeatMap));
}
else
{
results["Solution Similarities"].Value = similaritiesHeatMap;
}
// store similarities history
if (storeHistory)
{
if (!results.ContainsKey("Solution Similarities History"))
{
HeatMapHistory history = new HeatMapHistory();
history.Add(similaritiesHeatMap);
results.Add(new Result("Solution Similarities History", history));
}
else
{
((HeatMapHistory)results["Solution Similarities History"].Value).Add(similaritiesHeatMap);
}
}
// store average minimum, average and maximum similarity
if (!results.ContainsKey("Average Minimum Solution Similarity"))
{
results.Add(new Result("Average Minimum Solution Similarity", new DoubleValue(avgMinSimilarity)));
}
else
{
((DoubleValue)results["Average Minimum Solution Similarity"].Value).Value = avgMinSimilarity;
}
if (!results.ContainsKey("Average Average Solution Similarity"))
{
results.Add(new Result("Average Average Solution Similarity", new DoubleValue(avgAvgSimilarity)));
}
else
{
((DoubleValue)results["Average Average Solution Similarity"].Value).Value = avgAvgSimilarity;
}
if (!results.ContainsKey("Average Maximum Solution Similarity"))
{
results.Add(new Result("Average Maximum Solution Similarity", new DoubleValue(avgMaxSimilarity)));
}
else
{
((DoubleValue)results["Average Maximum Solution Similarity"].Value).Value = avgMaxSimilarity;
}
// store average minimum, average and maximum solution similarity data table
DataTable minAvgMaxSimilarityDataTable;
if (!results.ContainsKey("Average Minimum/Average/Maximum Solution Similarity"))
{
minAvgMaxSimilarityDataTable = new DataTable("Average Minimum/Average/Maximum Solution Similarity");
minAvgMaxSimilarityDataTable.VisualProperties.XAxisTitle = "Iteration";
minAvgMaxSimilarityDataTable.VisualProperties.YAxisTitle = "Solution Similarity";
minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Minimum Solution Similarity", null));
minAvgMaxSimilarityDataTable.Rows["Average Minimum Solution Similarity"].VisualProperties.StartIndexZero = true;
minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Average Solution Similarity", null));
minAvgMaxSimilarityDataTable.Rows["Average Average Solution Similarity"].VisualProperties.StartIndexZero = true;
minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Maximum Solution Similarity", null));
minAvgMaxSimilarityDataTable.Rows["Average Maximum Solution Similarity"].VisualProperties.StartIndexZero = true;
results.Add(new Result("Average Minimum/Average/Maximum Solution Similarity", minAvgMaxSimilarityDataTable));
}
else
{
minAvgMaxSimilarityDataTable = (DataTable)results["Average Minimum/Average/Maximum Solution Similarity"].Value;
}
minAvgMaxSimilarityDataTable.Rows["Average Minimum Solution Similarity"].Values.Add(avgMinSimilarity);
minAvgMaxSimilarityDataTable.Rows["Average Average Solution Similarity"].Values.Add(avgAvgSimilarity);
minAvgMaxSimilarityDataTable.Rows["Average Maximum Solution Similarity"].Values.Add(avgMaxSimilarity);
// store minimum, average, maximum similarities data table
DataTable minAvgMaxSimilaritiesDataTable = new DataTable("Minimum/Average/Maximum Solution Similarities");
minAvgMaxSimilaritiesDataTable.VisualProperties.XAxisTitle = "Solution Index";
minAvgMaxSimilaritiesDataTable.VisualProperties.YAxisTitle = "Solution Similarity";
minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Minimum Solution Similarity", null, minSimilarities));
minAvgMaxSimilaritiesDataTable.Rows["Minimum Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;
minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Average Solution Similarity", null, avgSimilarities));
minAvgMaxSimilaritiesDataTable.Rows["Average Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;
minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Maximum Solution Similarity", null, maxSimilarities));
minAvgMaxSimilaritiesDataTable.Rows["Maximum Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;
if (!results.ContainsKey("Minimum/Average/Maximum Solution Similarities"))
{
results.Add(new Result("Minimum/Average/Maximum Solution Similarities", minAvgMaxSimilaritiesDataTable));
}
else
{
results["Minimum/Average/Maximum Solution Similarities"].Value = minAvgMaxSimilaritiesDataTable;
}
// store minimum, average, maximum similarities history
if (storeHistory)
{
if (!results.ContainsKey("Minimum/Average/Maximum Solution Similarities History"))
{
DataTableHistory history = new DataTableHistory();
history.Add(minAvgMaxSimilaritiesDataTable);
results.Add(new Result("Minimum/Average/Maximum Solution Similarities History", history));
}
else
{
((DataTableHistory)results["Minimum/Average/Maximum Solution Similarities History"].Value).Add(minAvgMaxSimilaritiesDataTable);
}
}
}
return(base.Apply());
}
public override IOperation Apply()
{
int updateInterval = UpdateIntervalParameter.Value.Value;
IntValue updateCounter = UpdateCounterParameter.ActualValue;
// if counter does not yet exist then initialize it with update interval
// to make sure the solutions are analyzed on the first application of this operator
if (updateCounter == null)
{
updateCounter = new IntValue(updateInterval);
UpdateCounterParameter.ActualValue = updateCounter;
}
else
{
updateCounter.Value++;
}
//analyze solutions only every 'updateInterval' times
if (updateCounter.Value == updateInterval)
{
updateCounter.Value = 0;
bool max = MaximizationParameter.ActualValue.Value;
ItemArray <T> solutions = SolutionParameter.ActualValue;
ItemArray <DoubleValue> qualities = QualityParameter.ActualValue;
bool storeHistory = StoreHistoryParameter.Value.Value;
int count = solutions.Length;
if (count > 1)
{
// sort solutions by quality
T[] sortedSolutions = null;
if (max)
{
sortedSolutions = solutions
.Select((x, index) => new { Solution = x, Quality = qualities[index] })
.OrderByDescending(x => x.Quality)
.Select(x => x.Solution)
.ToArray();
}
else
{
sortedSolutions = solutions
.Select((x, index) => new { Solution = x, Quality = qualities[index] })
.OrderBy(x => x.Quality)
.Select(x => x.Solution)
.ToArray();
}
// calculate solution similarities
double[,] similarities = CalculateSimilarities(sortedSolutions);
// calculate minimum, average and maximum similarities
double similarity;
double[] minSimilarities = new double[count];
double[] avgSimilarities = new double[count];
double[] maxSimilarities = new double[count];
for (int i = 0; i < count; i++)
{
minSimilarities[i] = 1;
avgSimilarities[i] = 0;
maxSimilarities[i] = 0;
for (int j = 0; j < count; j++)
{
if (i != j)
{
similarity = similarities[i, j];
if ((similarity < 0) || (similarity > 1))
{
throw new InvalidOperationException("Solution similarities have to be in the interval [0;1].");
}
if (minSimilarities[i] > similarity)
{
minSimilarities[i] = similarity;
}
avgSimilarities[i] += similarity;
if (maxSimilarities[i] < similarity)
{
maxSimilarities[i] = similarity;
}
}
}
avgSimilarities[i] = avgSimilarities[i] / (count - 1);
}
double avgMinSimilarity = minSimilarities.Average();
double avgAvgSimilarity = avgSimilarities.Average();
double avgMaxSimilarity = maxSimilarities.Average();
// fetch results collection
ResultCollection results;
if (!ResultsParameter.ActualValue.ContainsKey(Name + " Results"))
{
results = new ResultCollection();
ResultsParameter.ActualValue.Add(new Result(Name + " Results", results));
}
else
{
results = (ResultCollection)ResultsParameter.ActualValue[Name + " Results"].Value;
}
// store similarities
HeatMap similaritiesHeatMap = new HeatMap(similarities, "Solution Similarities", 0.0, 1.0);
if (!results.ContainsKey("Solution Similarities"))
{
results.Add(new Result("Solution Similarities", similaritiesHeatMap));
}
else
{
results["Solution Similarities"].Value = similaritiesHeatMap;
}
// store similarities history
if (storeHistory)
{
if (!results.ContainsKey("Solution Similarities History"))
{
HeatMapHistory history = new HeatMapHistory();
history.Add(similaritiesHeatMap);
results.Add(new Result("Solution Similarities History", history));
}
else
{
((HeatMapHistory)results["Solution Similarities History"].Value).Add(similaritiesHeatMap);
}
}
// store average minimum, average and maximum similarity
if (!results.ContainsKey("Average Minimum Solution Similarity"))
{
results.Add(new Result("Average Minimum Solution Similarity", new DoubleValue(avgMinSimilarity)));
}
else
{
((DoubleValue)results["Average Minimum Solution Similarity"].Value).Value = avgMinSimilarity;
}
if (!results.ContainsKey("Average Average Solution Similarity"))
{
results.Add(new Result("Average Average Solution Similarity", new DoubleValue(avgAvgSimilarity)));
}
else
{
((DoubleValue)results["Average Average Solution Similarity"].Value).Value = avgAvgSimilarity;
}
if (!results.ContainsKey("Average Maximum Solution Similarity"))
{
results.Add(new Result("Average Maximum Solution Similarity", new DoubleValue(avgMaxSimilarity)));
}
else
{
((DoubleValue)results["Average Maximum Solution Similarity"].Value).Value = avgMaxSimilarity;
}
// store average minimum, average and maximum solution similarity data table
DataTable minAvgMaxSimilarityDataTable;
if (!results.ContainsKey("Average Minimum/Average/Maximum Solution Similarity"))
{
minAvgMaxSimilarityDataTable = new DataTable("Average Minimum/Average/Maximum Solution Similarity");
minAvgMaxSimilarityDataTable.VisualProperties.XAxisTitle = "Iteration";
minAvgMaxSimilarityDataTable.VisualProperties.YAxisTitle = "Solution Similarity";
minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Minimum Solution Similarity", null));
minAvgMaxSimilarityDataTable.Rows["Average Minimum Solution Similarity"].VisualProperties.StartIndexZero = true;
minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Average Solution Similarity", null));
minAvgMaxSimilarityDataTable.Rows["Average Average Solution Similarity"].VisualProperties.StartIndexZero = true;
minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Maximum Solution Similarity", null));
minAvgMaxSimilarityDataTable.Rows["Average Maximum Solution Similarity"].VisualProperties.StartIndexZero = true;
results.Add(new Result("Average Minimum/Average/Maximum Solution Similarity", minAvgMaxSimilarityDataTable));
}
else
{
minAvgMaxSimilarityDataTable = (DataTable)results["Average Minimum/Average/Maximum Solution Similarity"].Value;
}
minAvgMaxSimilarityDataTable.Rows["Average Minimum Solution Similarity"].Values.Add(avgMinSimilarity);
minAvgMaxSimilarityDataTable.Rows["Average Average Solution Similarity"].Values.Add(avgAvgSimilarity);
minAvgMaxSimilarityDataTable.Rows["Average Maximum Solution Similarity"].Values.Add(avgMaxSimilarity);
// store minimum, average, maximum similarities data table
DataTable minAvgMaxSimilaritiesDataTable = new DataTable("Minimum/Average/Maximum Solution Similarities");
minAvgMaxSimilaritiesDataTable.VisualProperties.XAxisTitle = "Solution Index";
minAvgMaxSimilaritiesDataTable.VisualProperties.YAxisTitle = "Solution Similarity";
minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Minimum Solution Similarity", null, minSimilarities));
minAvgMaxSimilaritiesDataTable.Rows["Minimum Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;
minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Average Solution Similarity", null, avgSimilarities));
minAvgMaxSimilaritiesDataTable.Rows["Average Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;
minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Maximum Solution Similarity", null, maxSimilarities));
minAvgMaxSimilaritiesDataTable.Rows["Maximum Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;
if (!results.ContainsKey("Minimum/Average/Maximum Solution Similarities"))
{
results.Add(new Result("Minimum/Average/Maximum Solution Similarities", minAvgMaxSimilaritiesDataTable));
}
else
{
results["Minimum/Average/Maximum Solution Similarities"].Value = minAvgMaxSimilaritiesDataTable;
}
// store minimum, average, maximum similarities history
if (storeHistory)
{
if (!results.ContainsKey("Minimum/Average/Maximum Solution Similarities History"))
{
DataTableHistory history = new DataTableHistory();
history.Add(minAvgMaxSimilaritiesDataTable);
results.Add(new Result("Minimum/Average/Maximum Solution Similarities History", history));
}
else
{
((DataTableHistory)results["Minimum/Average/Maximum Solution Similarities History"].Value).Add(minAvgMaxSimilaritiesDataTable);
}
}
}
}
return(base.Apply());
}
public override IOperation Apply() {
int updateInterval = UpdateIntervalParameter.Value.Value;
IntValue updateCounter = UpdateCounterParameter.ActualValue;
// if counter does not yet exist then initialize it with update interval
// to make sure the solutions are analyzed on the first application of this operator
if (updateCounter == null) {
updateCounter = new IntValue(updateInterval);
UpdateCounterParameter.ActualValue = updateCounter;
} else updateCounter.Value++;
//analyze solutions only every 'updateInterval' times
if (updateCounter.Value == updateInterval) {
updateCounter.Value = 0;
bool max = MaximizationParameter.ActualValue.Value;
ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
bool storeHistory = StoreHistoryParameter.Value.Value;
int count = CurrentScopeParameter.ActualValue.SubScopes.Count;
if (count > 1) {
// calculate solution similarities
var similarityMatrix = SimilarityCalculator.CalculateSolutionCrowdSimilarity(CurrentScopeParameter.ActualValue);
// sort similarities by quality
double[][] sortedSimilarityMatrix = null;
if (max)
sortedSimilarityMatrix = similarityMatrix
.Select((x, index) => new { Solutions = x, Quality = qualities[index] })
.OrderByDescending(x => x.Quality)
.Select(x => x.Solutions)
.ToArray();
else
sortedSimilarityMatrix = similarityMatrix
.Select((x, index) => new { Solutions = x, Quality = qualities[index] })
.OrderBy(x => x.Quality)
.Select(x => x.Solutions)
.ToArray();
double[,] similarities = new double[similarityMatrix.Length, similarityMatrix[0].Length];
for (int i = 0; i < similarityMatrix.Length; i++)
for (int j = 0; j < similarityMatrix[0].Length; j++)
similarities[i, j] = similarityMatrix[i][j];
// calculate minimum, average and maximum similarities
double similarity;
double[] minSimilarities = new double[count];
double[] avgSimilarities = new double[count];
double[] maxSimilarities = new double[count];
for (int i = 0; i < count; i++) {
minSimilarities[i] = 1;
avgSimilarities[i] = 0;
maxSimilarities[i] = 0;
for (int j = 0; j < count; j++) {
if (i != j) {
similarity = similarities[i, j];
if ((similarity < 0) || (similarity > 1))
throw new InvalidOperationException("Solution similarities have to be in the interval [0;1].");
if (minSimilarities[i] > similarity) minSimilarities[i] = similarity;
avgSimilarities[i] += similarity;
if (maxSimilarities[i] < similarity) maxSimilarities[i] = similarity;
}
}
avgSimilarities[i] = avgSimilarities[i] / (count - 1);
}
double avgMinSimilarity = minSimilarities.Average();
double avgAvgSimilarity = avgSimilarities.Average();
double avgMaxSimilarity = maxSimilarities.Average();
// fetch results collection
ResultCollection results;
if (!ResultsParameter.ActualValue.ContainsKey(Name + " Results")) {
results = new ResultCollection();
ResultsParameter.ActualValue.Add(new Result(Name + " Results", results));
} else {
results = (ResultCollection)ResultsParameter.ActualValue[Name + " Results"].Value;
}
// store similarities
HeatMap similaritiesHeatMap = new HeatMap(similarities, "Solution Similarities", 0.0, 1.0);
if (!results.ContainsKey("Solution Similarities"))
results.Add(new Result("Solution Similarities", similaritiesHeatMap));
else
results["Solution Similarities"].Value = similaritiesHeatMap;
// store similarities history
if (storeHistory) {
if (!results.ContainsKey("Solution Similarities History")) {
HeatMapHistory history = new HeatMapHistory();
history.Add(similaritiesHeatMap);
results.Add(new Result("Solution Similarities History", history));
} else {
((HeatMapHistory)results["Solution Similarities History"].Value).Add(similaritiesHeatMap);
}
}
// store average minimum, average and maximum similarity
if (!results.ContainsKey("Average Minimum Solution Similarity"))
results.Add(new Result("Average Minimum Solution Similarity", new DoubleValue(avgMinSimilarity)));
else
((DoubleValue)results["Average Minimum Solution Similarity"].Value).Value = avgMinSimilarity;
if (!results.ContainsKey("Average Average Solution Similarity"))
results.Add(new Result("Average Average Solution Similarity", new DoubleValue(avgAvgSimilarity)));
else
((DoubleValue)results["Average Average Solution Similarity"].Value).Value = avgAvgSimilarity;
if (!results.ContainsKey("Average Maximum Solution Similarity"))
results.Add(new Result("Average Maximum Solution Similarity", new DoubleValue(avgMaxSimilarity)));
else
((DoubleValue)results["Average Maximum Solution Similarity"].Value).Value = avgMaxSimilarity;
// store average minimum, average and maximum solution similarity data table
DataTable minAvgMaxSimilarityDataTable;
if (!results.ContainsKey("Average Minimum/Average/Maximum Solution Similarity")) {
minAvgMaxSimilarityDataTable = new DataTable("Average Minimum/Average/Maximum Solution Similarity");
minAvgMaxSimilarityDataTable.VisualProperties.XAxisTitle = "Iteration";
minAvgMaxSimilarityDataTable.VisualProperties.YAxisTitle = "Solution Similarity";
minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Minimum Solution Similarity", null));
minAvgMaxSimilarityDataTable.Rows["Average Minimum Solution Similarity"].VisualProperties.StartIndexZero = true;
minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Average Solution Similarity", null));
minAvgMaxSimilarityDataTable.Rows["Average Average Solution Similarity"].VisualProperties.StartIndexZero = true;
minAvgMaxSimilarityDataTable.Rows.Add(new DataRow("Average Maximum Solution Similarity", null));
minAvgMaxSimilarityDataTable.Rows["Average Maximum Solution Similarity"].VisualProperties.StartIndexZero = true;
results.Add(new Result("Average Minimum/Average/Maximum Solution Similarity", minAvgMaxSimilarityDataTable));
} else {
minAvgMaxSimilarityDataTable = (DataTable)results["Average Minimum/Average/Maximum Solution Similarity"].Value;
}
minAvgMaxSimilarityDataTable.Rows["Average Minimum Solution Similarity"].Values.Add(avgMinSimilarity);
minAvgMaxSimilarityDataTable.Rows["Average Average Solution Similarity"].Values.Add(avgAvgSimilarity);
minAvgMaxSimilarityDataTable.Rows["Average Maximum Solution Similarity"].Values.Add(avgMaxSimilarity);
// store minimum, average, maximum similarities data table
DataTable minAvgMaxSimilaritiesDataTable = new DataTable("Minimum/Average/Maximum Solution Similarities");
minAvgMaxSimilaritiesDataTable.VisualProperties.XAxisTitle = "Solution Index";
minAvgMaxSimilaritiesDataTable.VisualProperties.YAxisTitle = "Solution Similarity";
minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Minimum Solution Similarity", null, minSimilarities));
minAvgMaxSimilaritiesDataTable.Rows["Minimum Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;
minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Average Solution Similarity", null, avgSimilarities));
minAvgMaxSimilaritiesDataTable.Rows["Average Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;
minAvgMaxSimilaritiesDataTable.Rows.Add(new DataRow("Maximum Solution Similarity", null, maxSimilarities));
minAvgMaxSimilaritiesDataTable.Rows["Maximum Solution Similarity"].VisualProperties.ChartType = DataRowVisualProperties.DataRowChartType.Points;
if (!results.ContainsKey("Minimum/Average/Maximum Solution Similarities")) {
results.Add(new Result("Minimum/Average/Maximum Solution Similarities", minAvgMaxSimilaritiesDataTable));
} else {
results["Minimum/Average/Maximum Solution Similarities"].Value = minAvgMaxSimilaritiesDataTable;
}
// store minimum, average, maximum similarities history
if (storeHistory) {
if (!results.ContainsKey("Minimum/Average/Maximum Solution Similarities History")) {
DataTableHistory history = new DataTableHistory();
history.Add(minAvgMaxSimilaritiesDataTable);
results.Add(new Result("Minimum/Average/Maximum Solution Similarities History", history));
} else {
((DataTableHistory)results["Minimum/Average/Maximum Solution Similarities History"].Value).Add(minAvgMaxSimilaritiesDataTable);
}
}
}
}
return base.Apply();
}
protected HeatMap(HeatMap original, Cloner cloner)
: base(original, cloner) {
this.title = original.title;
this.minimum = original.minimum;
this.maximum = original.maximum;
}