public ScatterPlot CreateScatterPlot(string variableNameX, string variableNameY, string variableNameColor = "-") {
ScatterPlot scatterPlot = new ScatterPlot();
IList<double> xValues = PreprocessingData.GetValues<double>(PreprocessingData.GetColumnIndex(variableNameX));
IList<double> yValues = PreprocessingData.GetValues<double>(PreprocessingData.GetColumnIndex(variableNameY));
if (variableNameColor == null || variableNameColor == "-") {
List<Point2D<double>> points = new List<Point2D<double>>();
for (int i = 0; i < xValues.Count; i++) {
Point2D<double> point = new Point2D<double>(xValues[i], yValues[i]);
points.Add(point);
}
ScatterPlotDataRow scdr = new ScatterPlotDataRow(variableNameX + " - " + variableNameY, "", points);
scatterPlot.Rows.Add(scdr);
} else {
var colorValues = PreprocessingData.GetValues<double>(PreprocessingData.GetColumnIndex(variableNameColor));
var data = xValues.Zip(yValues, (x, y) => new { x, y }).Zip(colorValues, (v, c) => new { v.x, v.y, c }).ToList();
var gradients = ColorGradient.Colors;
int curGradient = 0;
int numColors = colorValues.Distinct().Count();
foreach (var colorValue in colorValues.Distinct()) {
var values = data.Where(x => x.c == colorValue);
var row = new ScatterPlotDataRow(
variableNameX + " - " + variableNameY + " (" + colorValue + ")",
"",
values.Select(v => new Point2D<double>(v.x, v.y)),
new ScatterPlotDataRowVisualProperties() { Color = gradients[curGradient] });
curGradient += gradients.Count / numColors;
scatterPlot.Rows.Add(row);
}
}
return scatterPlot;
}
public ScatterPlot CreateScatterPlot(string variableNameX, string variableNameY) {
ScatterPlot scatterPlot = new ScatterPlot();
IList<double> xValues = PreprocessingData.GetValues<double>(PreprocessingData.GetColumnIndex(variableNameX));
IList<double> yValues = PreprocessingData.GetValues<double>(PreprocessingData.GetColumnIndex(variableNameY));
List<Point2D<double>> points = new List<Point2D<double>>();
for (int i = 0; i < xValues.Count; i++) {
Point2D<double> point = new Point2D<double>(xValues[i], yValues[i]);
points.Add(point);
}
ScatterPlotDataRow scdr = new ScatterPlotDataRow(variableNameX + " - " + variableNameY, "", points);
scatterPlot.Rows.Add(scdr);
return scatterPlot;
}
public override IOperation Apply()
{
int updateInterval = UpdateIntervalParameter.Value.Value;
IntValue updateCounter = UpdateCounterParameter.ActualValue;
if (updateCounter == null)
{
updateCounter = new IntValue(updateInterval);
UpdateCounterParameter.ActualValue = updateCounter;
}
else
{
updateCounter.Value++;
}
if (updateCounter.Value == updateInterval)
{
updateCounter.Value = 0;
bool max = MaximizationParameter.ActualValue.Value;
ItemArray <T> solutions = SolutionParameter.ActualValue;
double[] qualities = QualityParameter.ActualValue.Select(x => x.Value).ToArray();
T bestKnownSolution = BestKnownSolutionParameter.ActualValue;
bool storeHistory = StoreHistoryParameter.Value.Value;
// calculate index of current best solution
int bestIndex = -1;
if (!max)
{
bestIndex = qualities
.Select((x, i) => new { Index = i, Value = x })
.OrderBy(x => x.Value)
.First().Index;
}
else
{
bestIndex = qualities
.Select((x, i) => new { Index = i, Value = x })
.OrderByDescending(x => x.Value)
.First().Index;
}
// calculate allels of current best and (if available) best known solution
Allele[] bestAlleles = CalculateAlleles(solutions[bestIndex]);
Allele[] bestKnownAlleles = null;
if (bestKnownSolution != null)
{
bestKnownAlleles = CalculateAlleles(bestKnownSolution);
}
// calculate allele frequencies
var frequencies = solutions.SelectMany((s, index) => CalculateAlleles(s).Select(a => new { Allele = a, Quality = qualities[index] })).
GroupBy(x => x.Allele.Id).
Select(x => new AlleleFrequency(x.Key,
x.Count() / ((double)solutions.Length),
x.Average(a => a.Allele.Impact),
x.Average(a => a.Quality),
bestKnownAlleles == null ? false : bestKnownAlleles.Any(a => a.Id == x.Key),
bestAlleles.Any(a => a.Id == x.Key)));
// calculate dummy allele frequencies of alleles of best known solution which did not occur
if (bestKnownAlleles != null)
{
var bestKnownFrequencies = bestKnownAlleles.Select(x => new AlleleFrequency(x.Id, 0, x.Impact, 0, true, false)).Except(frequencies, new AlleleFrequencyIdEqualityComparer());
frequencies = frequencies.Concat(bestKnownFrequencies);
}
// 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 allele frequencies
AlleleFrequencyCollection frequenciesCollection = new AlleleFrequencyCollection(frequencies);
if (!results.ContainsKey("Allele Frequencies"))
{
results.Add(new Result("Allele Frequencies", frequenciesCollection));
}
else
{
results["Allele Frequencies"].Value = frequenciesCollection;
}
// store allele frequencies history
if (storeHistory)
{
if (!results.ContainsKey("Allele Frequencies History"))
{
AlleleFrequencyCollectionHistory history = new AlleleFrequencyCollectionHistory();
history.Add(frequenciesCollection);
results.Add(new Result("Allele Frequencies History", history));
}
else
{
((AlleleFrequencyCollectionHistory)results["Allele Frequencies History"].Value).Add(frequenciesCollection);
}
}
// store alleles data table
DataTable allelesTable;
if (!results.ContainsKey("Alleles"))
{
allelesTable = new DataTable("Alleles");
allelesTable.VisualProperties.XAxisTitle = "Iteration";
allelesTable.VisualProperties.YAxisTitle = "Number of Alleles";
allelesTable.VisualProperties.SecondYAxisTitle = "Number of Alleles";
allelesTable.Rows.Add(new DataRow("Unique Alleles"));
allelesTable.Rows["Unique Alleles"].VisualProperties.StartIndexZero = true;
allelesTable.Rows.Add(new DataRow("Unique Alleles of Best Known Solution", null));
allelesTable.Rows["Unique Alleles of Best Known Solution"].VisualProperties.SecondYAxis = true;
allelesTable.Rows["Unique Alleles of Best Known Solution"].VisualProperties.StartIndexZero = true;
allelesTable.Rows.Add(new DataRow("Fixed Alleles", null));
allelesTable.Rows["Fixed Alleles"].VisualProperties.SecondYAxis = true;
allelesTable.Rows["Fixed Alleles"].VisualProperties.StartIndexZero = true;
allelesTable.Rows.Add(new DataRow("Fixed Alleles of Best Known Solution", null));
allelesTable.Rows["Fixed Alleles of Best Known Solution"].VisualProperties.SecondYAxis = true;
allelesTable.Rows["Fixed Alleles of Best Known Solution"].VisualProperties.StartIndexZero = true;
allelesTable.Rows.Add(new DataRow("Lost Alleles of Best Known Solution", null));
allelesTable.Rows["Lost Alleles of Best Known Solution"].VisualProperties.SecondYAxis = true;
allelesTable.Rows["Lost Alleles of Best Known Solution"].VisualProperties.StartIndexZero = true;
results.Add(new Result("Alleles", allelesTable));
}
else
{
allelesTable = (DataTable)results["Alleles"].Value;
}
int fixedAllelesCount = frequenciesCollection.Where(x => x.Frequency == 1).Count();
var relevantAlleles = frequenciesCollection.Where(x => x.ContainedInBestKnownSolution);
int relevantAllelesCount = relevantAlleles.Count();
int fixedRelevantAllelesCount = relevantAlleles.Where(x => x.Frequency == 1).Count();
int lostRelevantAllelesCount = relevantAlleles.Where(x => x.Frequency == 0).Count();
int uniqueRelevantAllelesCount = relevantAllelesCount - lostRelevantAllelesCount;
allelesTable.Rows["Unique Alleles"].Values.Add(frequenciesCollection.Count);
allelesTable.Rows["Unique Alleles of Best Known Solution"].Values.Add(uniqueRelevantAllelesCount);
allelesTable.Rows["Fixed Alleles"].Values.Add(fixedAllelesCount);
allelesTable.Rows["Fixed Alleles of Best Known Solution"].Values.Add(fixedRelevantAllelesCount);
allelesTable.Rows["Lost Alleles of Best Known Solution"].Values.Add(lostRelevantAllelesCount);
// store alleles values
if (!results.ContainsKey("Unique Alleles"))
{
results.Add(new Result("Unique Alleles", new DoubleValue(frequenciesCollection.Count)));
}
else
{
((DoubleValue)results["Unique Alleles"].Value).Value = frequenciesCollection.Count;
}
if (!results.ContainsKey("Unique Alleles of Best Known Solution"))
{
results.Add(new Result("Unique Alleles of Best Known Solution", new DoubleValue(uniqueRelevantAllelesCount)));
}
else
{
((DoubleValue)results["Unique Alleles of Best Known Solution"].Value).Value = uniqueRelevantAllelesCount;
}
if (!results.ContainsKey("Fixed Alleles"))
{
results.Add(new Result("Fixed Alleles", new DoubleValue(fixedAllelesCount)));
}
else
{
((DoubleValue)results["Fixed Alleles"].Value).Value = fixedAllelesCount;
}
if (!results.ContainsKey("Fixed Alleles of Best Known Solution"))
{
results.Add(new Result("Fixed Alleles of Best Known Solution", new DoubleValue(fixedRelevantAllelesCount)));
}
else
{
((DoubleValue)results["Fixed Alleles of Best Known Solution"].Value).Value = fixedRelevantAllelesCount;
}
if (!results.ContainsKey("Lost Alleles of Best Known Solution"))
{
results.Add(new Result("Lost Alleles of Best Known Solution", new DoubleValue(lostRelevantAllelesCount)));
}
else
{
((DoubleValue)results["Lost Alleles of Best Known Solution"].Value).Value = lostRelevantAllelesCount;
}
// calculate contained alleles of best known solution and relative quality
if (bestKnownAlleles != null)
{
double qualityRange = Math.Abs(qualities.Max() - qualities.Min());
var points = solutions.Select((s, index) => new Point2D <double>(CalculateAlleles(s).Intersect(bestKnownAlleles, new AlleleIdEqualityComparer()).Count(),
Math.Abs(qualities[index] - qualities[bestIndex]) / qualityRange));
var avgContainedReleventAlleles = points.Select(x => x.X).Average();
var plot = new ScatterPlot("Contained Alleles of Best Known Solution and Relative Solution Qualtiy", null);
plot.VisualProperties.XAxisTitle = "Contained Alleles of Best Known Solution";
plot.VisualProperties.YAxisTitle = "Relative Solution Quality";
plot.VisualProperties.XAxisMinimumAuto = false;
plot.VisualProperties.XAxisMinimumFixedValue = 0.0;
plot.VisualProperties.XAxisMaximumAuto = false;
plot.VisualProperties.XAxisMaximumFixedValue = bestKnownAlleles.Length;
plot.VisualProperties.YAxisMinimumAuto = false;
plot.VisualProperties.YAxisMinimumFixedValue = 0.0;
plot.VisualProperties.YAxisMaximumAuto = false;
plot.VisualProperties.YAxisMaximumFixedValue = 1.0;
var row = new ScatterPlotDataRow("Solutions of Current Generation", null, points);
row.VisualProperties.PointStyle = ScatterPlotDataRowVisualProperties.ScatterPlotDataRowPointStyle.Circle;
row.VisualProperties.PointSize = 5;
plot.Rows.Add(row);
if (!results.ContainsKey("Scatter Plot"))
{
results.Add(new Result("Scatter Plot", plot));
}
else
{
results["Scatter Plot"].Value = plot;
}
if (storeHistory)
{
if (!results.ContainsKey("Scatter Plot History"))
{
results.Add(new Result("Scatter Plot History", new ScatterPlotHistory()));
}
((ScatterPlotHistory)results["Scatter Plot History"].Value).Add(plot);
}
if (!allelesTable.Rows.ContainsKey("Average Contained Alleles of Best Known Solution"))
{
allelesTable.Rows.Add(new DataRow("Average Contained Alleles of Best Known Solution", null));
allelesTable.Rows["Average Contained Alleles of Best Known Solution"].VisualProperties.SecondYAxis = true;
allelesTable.Rows["Average Contained Alleles of Best Known Solution"].VisualProperties.StartIndexZero = true;
}
allelesTable.Rows["Average Contained Alleles of Best Known Solution"].Values.Add(avgContainedReleventAlleles);
if (!results.ContainsKey("Average Contained Alleles of Best Known Solution"))
{
results.Add(new Result("Average Contained Alleles of Best Known Solution", new DoubleValue(avgContainedReleventAlleles)));
}
else
{
((DoubleValue)results["Average Contained Alleles of Best Known Solution"].Value).Value = avgContainedReleventAlleles;
}
}
}
return(base.Apply());
}
protected ScatterPlot(ScatterPlot original, Cloner cloner)
: base(original, cloner)
{
VisualProperties = cloner.Clone(original.visualProperties);
Rows = cloner.Clone(original.rows);
}
//Extract variable names from scatter plot and set them in content
private void setVariablesInContentFromScatterPlot(ScatterPlotContent scatterContent, ScatterPlot scatterPlot) {
// only one data row should be in scatter plot
if (scatterPlot.Rows.Count == 1) {
string[] variables = scatterPlot.Rows.ElementAt(0).Name.Split(new string[] { " - " }, StringSplitOptions.None); // extract variable names from string
scatterContent.SelectedXVariable = variables[0];
scatterContent.SelectedYVariable = variables[1];
}
}
protected ScatterPlot(ScatterPlot original, Cloner cloner)
: base(original, cloner) {
VisualProperties = cloner.Clone(original.visualProperties);
Rows = cloner.Clone(original.rows);
}