public void Initialise()
{
// A dictionary of week-events
Events = new EventCollection();
// Read in the Week 32 logs
KMLReader w32_reader = new KMLReader(ROOT_DIR + "data\\L_wk32_drops.kml");
Events.AddRange(w32_reader.GetCallLogs());
// Read in the Week 33 logs
KMLReader w33_reader = new KMLReader(ROOT_DIR + "data\\L_wk33_drops.kml");
Events.AddRange(w33_reader.GetCallLogs());
// Read in the Week 34 logs
KMLReader w34_reader = new KMLReader(ROOT_DIR + "data\\L_wk34_drops.kml");
Events.AddRange(w34_reader.GetCallLogs());
// Read in the Week 35 logs
KMLReader w35_reader = new KMLReader(ROOT_DIR + "data\\L_wk35_drops.kml");
Events.AddRange(w35_reader.GetCallLogs());
// Initialise the Multi-Product Analysis Object
Analysis = new MultiProductAnalysis();
Analysis.AddRange(Events);
// Cluster the data
Analysis.Cluster(EPS, MIN_POINTS);
// Analyse all weeks
Analysis.AnalyseProducts();
}
/// <summary>
/// This method will cluster and analyse a given event collection based
/// upon a product approach.
/// </summary>
/// <param name="collection">The EventCollection to be clustered and analysed</param>
private static void PerformProductAnalysis(EventCollection collection)
{
// Output directory
String output = InputArguments["output"];
// Create a Multi-Week Analysis object
MultiProductAnalysis multi = new MultiProductAnalysis();
multi.AddRange(collection);
// Obtain the EPS distance value
double eps = GetEPSInput();
// Obtain the Minimum Number of Objects per cluster value
int min = GetMinPointsInput();
// Cluster the Multi-Week Data
multi.Cluster(eps, min);
// Analyse the Multi-Week Data
multi.AnalyseProducts();
// Output the KML file
String kml_output = GenerateOutputName(".kmz");
multi.GenerateKMZ(kml_output);
// Save the results to the output directory
bool minify = InputArguments.ContainsKey("jsminify") ? true : false;
multi.CreateProductsAnalysisJSON(output, minify);
}