public void open_xml()
{
OpenFileDialog openFileDialog1 = new OpenFileDialog
{
InitialDirectory = @"C:\",
Title = "Browse Text Files",
CheckFileExists = true,
CheckPathExists = true,
DefaultExt = "xml",
Filter = "xml files (*.xml)|*.xml",
FilterIndex = 2,
RestoreDirectory = true,
ReadOnlyChecked = true,
ShowReadOnly = true
};
// check if file path is correct
if (openFileDialog1.ShowDialog() == true)
{
file_path = openFileDialog1.FileName; // initial file path field
//StreamReader sr = new StreamReader(file_path);
readXML((string)file_path);
create_dict();
find_most_corralated();
TimeSeries ts1 = new TimeSeries((string)file_path_csv, chunks);
SimpleAnomalyDetector s = new SimpleAnomalyDetector();
TimeSeries ts = new TimeSeries((string)file_path2, chunks);
s.learnNormal(ts);
List <AnomalyReport> a = s.detect(ts1);
}
}
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);
CorrelatedFeatures c = s.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();
}
// size vector
int size = ts_normal.get_dict()[features.IndexOf(chosen_feature)].Count;
// create circle ****************************************************************
List <DataPoint> learn_points = circle_to_points(c.Center.x, c.Center.y, c.Threshold);
Circle_Points = learn_points;
NotifyPropertyChanged("Circle_Points");
//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");
// the point of the detect
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");
}
// anomaly.get_points(ts_normal.get_dict()[features.IndexOf(chosen_feature)], ts_normal.get_dict()[ts_normal.get]
}