/******************************************************************************
 *  Compilation:  javac SparseMatrix.java
 *  Execution:    java SparseMatrix
 *  
 *  A sparse, square matrix, implementing using two arrays of sparse
 *  vectors, one representation for the rows and one for the columns.
 *
 *  For matrix-matrix product, we might also want to store the
 *  column representation.
 *
 ******************************************************************************/


package network;

import java.util.HashSet;
import java.util.Set;

public class SparseMatrix {
    private final int N;           // N-by-N matrix
    private SparseVector[] rows;   // the rows, each row is a sparse vector

    // initialize an N-by-N matrix of all 0s
    public SparseMatrix(int N) {
        this.N  = N;
        rows = new SparseVector[N];
        for (int i = 0; i < N; i++)
            rows[i] = new SparseVector(N);
    }

    public Set<Integer> getKey(int a) {
    	return rows[a].getKeys();
    }
    
    public SparseVector getNeibor(int a) {
    	return rows[a];
    }
    
    // put A[i][j] = value
    public void put(int i, int j, double value) {
        if (i < 0 || i >= N) throw new RuntimeException("Illegal index");
        if (j < 0 || j >= N) throw new RuntimeException("Illegal index");
        rows[i].put(j, value);
    }

    // return A[i][j]
    public double get(int i, int j) {
        if (i < 0 || i >= N) throw new RuntimeException("Illegal index");
        if (j < 0 || j >= N) throw new RuntimeException("Illegal index");
        return rows[i].get(j);
    }

    // return the number of nonzero entries (not the most efficient implementation)
    public int nnz() { 
        int sum = 0;
        for (int i = 0; i < N; i++)
            sum += rows[i].nnz();
        return sum;
    }
    
    public int size() { 
        return N;
    }

    // return the matrix-vector product b = Ax
    public SparseVector times(SparseVector x) {
        SparseMatrix A = this;
        if (N != x.size()) throw new RuntimeException("Dimensions disagree");
        SparseVector b = new SparseVector(N);
        for (int i = 0; i < N; i++)
            b.put(i, A.rows[i].dot(x));
        return b;
    }

    // return C = A + B
    public SparseMatrix plus(SparseMatrix B) {
        SparseMatrix A = this;
        if (A.N != B.N) throw new RuntimeException("Dimensions disagree");
        SparseMatrix C = new SparseMatrix(N);
        for (int i = 0; i < N; i++)
            C.rows[i] = A.rows[i].plus(B.rows[i]);
        return C;
    }


    // return a string representation
    public String toString() {
        StringBuilder s = new StringBuilder();
        s.append("N = " + N + ", nonzeros = " + nnz() + "\n");
        for (int i = 0; i < N; i++) {
            s.append(i + ": " + rows[i] + "\n");
        }
        return s.toString();
    }


    // test client
    public static void main(String[] args) {
        SparseMatrix A = new SparseMatrix(5);
        SparseVector x = new SparseVector(5);
        A.put(0, 0, 1.0);
        A.put(1, 1, 1.0);
        A.put(2, 2, 1.0);
        A.put(3, 3, 1.0);
        A.put(4, 4, 1.0);
        A.put(2, 4, 0.3);
        x.put(0, 0.75);
        x.put(2, 0.11);
        System.out.println("x     : " + x);
        System.out.println("A     : " + A);
        System.out.println("Ax    : " + A.times(x));
        System.out.println("A + A : " + A.plus(A));
    }

}