Loading the data

In the first step, we'll need to load the data from text files to a Java object. The files are stored in a folder, and each file contains one time series, with values per line. We'll load them into a Double list, as follows:

String filePath = "chap07/ydata/A1Benchmark/real"; 
List<List<Double>> rawData = new ArrayList<List<Double>>(); 

We will need the min and max value for histogram normalization; so, let's collect them in this data pass:

double max = Double.MIN_VALUE; 
double min = Double.MAX_VALUE; 
 
for(int i = 1; i<= 67; i++){ 
  List<Double> sample = new ArrayList<Double>(); 
  BufferedReader reader = new BufferedReader(new 
     FileReader(filePath+i+".csv")); 
   
  boolean isAnomaly = false; 
  reader.readLine(); 
  while(reader.ready()){ 
    String line[] = reader.readLine().split(","); 
    double value = Double.parseDouble(line[1]); 
    sample.add(value); 
     
    max = Math.max(max, value); 
    min = Double.min(min, value); 
     
    if(line[2] == "1") 
      isAnomaly = true; 
     
  } 
  System.out.println(isAnomaly); 
  reader.close(); 
   
  rawData.add(sample); 
} 

The data has been loaded. Next, let's move on to histograms.