public void find_exceptions_points(string csv_learn, string csv_detect, List <string> features, string chosen_feature)
{
Anomaly_detector anomaly = new Anomaly_detector();
SimpleAnomalyDetector s = new SimpleAnomalyDetector();
this.sd = s;
ts_normal = new TimeSeries((string)csv_learn, features);
sd.learnNormal(ts_normal);
ts_detect = new TimeSeries((string)csv_detect, features);
anomaly_reports = sd.detect(ts_detect);
for (int i = 0; i < anomaly_reports.Count; i++)
{
Line_Reg_Points.Add(new DataPoint(anomaly_reports[i].timeStep, 0));
}
NotifyPropertyChanged("Line_Reg_Points");
}
public void updateChoose(string csv_learn, string csv_detect, List <string> features, string chosen_feature)
{
/*Anomaly_detector anomaly = new Anomaly_detector();
* SimpleAnomalyDetector s = new SimpleAnomalyDetector();
* this.sd = s;
* ts_normal = new TimeSeries((string)csv_learn, features);
* s.learnNormal(ts_normal);
* TimeSeries ts_detect = new TimeSeries((string)csv_detect, features);
* anomaly_reports = s.detect(ts_detect);*/
Anomaly_detector anomaly = new Anomaly_detector();
SimpleAnomalyDetector s = new SimpleAnomalyDetector();
this.sd = s;
ts_normal = new TimeSeries((string)csv_learn, features);
sd.learnNormal(ts_normal);
ts_detect = new TimeSeries((string)csv_detect, features);
anomaly_reports = sd.detect(ts_detect);
for (int i = 0; i < anomaly_reports.Count; i++)
{
Line_Reg_Points.Add(new DataPoint(anomaly_reports[i].timeStep, 0));
}
NotifyPropertyChanged("Line_Reg_Points");
CorrelatedFeatures c = sd.get_correlated(chosen_feature);
if (c != null)
{
string second_cor;
if (c.get_feature1() == chosen_feature)
{
second_cor = c.get_feature2();
}
else
{
second_cor = c.get_feature1();
}
int size = ts_normal.get_dict()[features.IndexOf(chosen_feature)].Count;
//sap-
List <DataPoint> learn_points = line_to_points(c.get_line_reg(), size, ts_detect.get_dict()[features.IndexOf(chosen_feature)], ts_detect.get_dict()[features.IndexOf(second_cor)]);
Line_Reg_Points = learn_points;
NotifyPropertyChanged("Line_Reg_Points");
//same
List <DataPoint> detected_points = new List <DataPoint>();
for (int i = 0; i < anomaly_reports.Count; i++)
{
if (anomaly_reports[i].get_feature1() == chosen_feature)
{
float x = ts_detect.get_dict()[features.IndexOf(chosen_feature)][(int)anomaly_reports[i].timeStep];
float y = ts_detect.get_dict()[features.IndexOf(second_cor)][(int)anomaly_reports[i].timeStep];
detected_points.Add(new DataPoint(x, y));
}
else
{
float x = ts_detect.get_dict()[features.IndexOf(second_cor)][(int)anomaly_reports[i].timeStep];
float y = ts_detect.get_dict()[features.IndexOf(chosen_feature)][(int)anomaly_reports[i].timeStep];
detected_points.Add(new DataPoint(x, y));
}
}
Anomaly_Points = detected_points;
NotifyPropertyChanged("Anomaly_Points");
}
else
{
Anomaly_Points = new List <DataPoint>();
Line_Reg_Points = new List <DataPoint>();
}
}
