import java.io.*;
import java.util.*;
import java.lang.*;
import Jama.*;
public class pcafaces{
    public static void main(String args[]){
    double[][] xmatrix = new double[644][280];
    double sum = 0;
    //int pixels=644;
    //int photos=280;
    double diagSum = 0;
    double dimension = 0;
    int r = 0;
    double[][] amatrix = new double[644][280];
    //file handlers
    Matrix Y;
    Matrix zDash;
    if(args.length!=4){
        throw new NullPointerException();
        }
    String trainPath = args[0];
    String testPath = args[1];
    String varth = args[2];
    String k = args[3];
    int realK =(Integer.parseInt(k));
    for(int i=0;i<40;i++){
        for(int j=0;j<7;j++){
        try{
        BufferedReader in = new BufferedReader(new FileReader(trainPath+"/s"+i+"_"+j+".pgm"));
        in.readLine(); // This reads 'P2'.
        in.readLine(); // This reads the comment.
        in.readLine(); // This reads the image dimensions.
        in.readLine(); // This reads the intensity range.
    for(int p = 0;p<644;p++){
        xmatrix[p][i*7+j]= Double.parseDouble(in.readLine());
        }
        //System.out.println(xmatrix[300][170]);
        in.close();
        }catch(IOException e){}
            }
        }
        double[][] xMean = new double[644][1];
        double[][] xBar = new double[644][280];
        for(int i=0;i<644;i++){
            for(int j=0;j<280;j++){
                sum = i+j;
                xMean[i][0] = sum*(1/(280));
                xBar[i][j] = xmatrix[i][j] - xMean[i][0];
        }
    }

        //Initialises matrix A with the values in the double array vals.
        Matrix A = new Matrix(xBar);
        // Invokes SVD from the Jama package.
        SingularValueDecomposition s = A.svd();
        Matrix D = s.getS();//get sigma diagonal matrix and add values to sum
        for(int i=0;i<280;i++){
        diagSum+=D.get(i,i);
        }
        for(int i=0;i<280;i++){
        dimension += D.get(i,i);            //(dimension/diagSum)*100
        if(((dimension/diagSum)*100)>=Double.parseDouble(varth)){
            r = i;
            break;
            }
        }
        Matrix B = new Matrix(xMean);
        Matrix U = s.getU();
        Matrix Ur = U.getMatrix(0, U.getRowDimension()-1, 0, r);
        Y = ((Ur).transpose()).times(A);



    for(int i1=0;i1<40;i1++){
        for(int j1=0;j1<3;j1++){
            try{
        BufferedReader br = new BufferedReader(new FileReader(testPath+"/s"+i1+"_"+j1+".pgm"));
        br.readLine(); // This reads 'P2'.
        br.readLine(); // This reads the comment.
        br.readLine(); // This reads the image dimensions.
        br.readLine(); // This reads the intensity range.


        double[][] zmatrix = new double[23*28][1];
    for(int p =0;p<644;p++){
        zmatrix[p][0]= Double.parseDouble(br.readLine());
        }
        Matrix Z = new Matrix(zmatrix);
        zDash = Ur.transpose().times(Z.minus(B));

        //perform comparison with test files and train files
    /*8. Perform classification using Z' and Y , e.g., find the K nearest
    neighbours of Z' among Y .*/
    double distance;
    int[] label = new int[realK];
    double[] nndis = new double[realK];
    for(int i=0;i<280;i++){
            distance=0;
        for(int j=0;j<r;j++){
            distance +=Math.pow((zDash.get(j,0)-(Y.get(j,i))),2);
            }
                for(int j=0;j<realK;j++){
                    if(distance<nndis[j]){
                        for(int l=realK-2;l>=j;l--){
                        nndis[l+1]=nndis[l];
                        label[l + 1]  = label[l];//nnlab[k]=total photos/photosper person
                        }
                    nndis[realK] = distance;
                    label[realK] = i/7;
                    break;
                    }
                }
            }
        //return majority value of label

        double max=0;
        int index=0;
        boolean check = false;
        int[] result = new int[40];
        double maxResult=0;
        for (int i = 0; i <40; ++i) {
         result[i]= 0;
         }
        for (int i = 0; i<realK; i++) {
            result[label[i]]++;
            }
        for(int i=0;i<40;i++){
            if (result[i] > maxResult) {
            maxResult = result[i];
            index = result[i];
            check = true;
            }
        }
    if(check){
    System.out.println(-1);
        }else{
    System.out.println(result[index]);
        }
        br.close();
        }catch(IOException e){}
            }
        }
    }
}