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];
        double[][] xBar = new double[644][280];
        for(int i=0;i<644;i++){
            sum = 0;
            for(int j=0;j<280;j++){
                sum = sum +xmatrix[i][j];
            }
            xMean[i] = sum/(280);
            for(int j=0;j<280;j++){
                xBar[i][j] = xmatrix[i][j] - xMean[i];
            }
        }

        //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());
                        zmatrix[p][0] = zmatrix[p][0]-xMean[p];
                    }
                    //maybe put above line in seperate for loop.....
                    Matrix Z = new Matrix(zmatrix);
                    zDash = Ur.transpose().times(Z);

                    //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 = true;
                    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 = i;
                            check = false;
                        }
                        else if(result[i]==maxResult){
                            maxResult = result[i];
                            index = i;
                            check = true;
                        }
                    }
                    if(check){
                        System.out.println(-1);
                    }else{
                        System.out.println(result[index]);
                    }
                    br.close();
                }catch(IOException e){}
            }
        }
    }
}