code: public boolean computeDirect( DMatrixRMaj A ) {
  
          initPower(A);
  
          boolean converged = false;
  
          for( int i = 0; i < maxIterations && !converged; i++ ) {
  //            q0.print();
              
              CommonOps_DDRM.mult(A,q0,q1);
              double s = NormOps_DDRM.normPInf(q1);
              CommonOps_DDRM.divide(q1,s,q2);
  
              converged = checkConverged(A);
          }
  
          return converged;
      }
docs: This method computes the eigen vector with the largest eigen value by using the
  direct power method. This technique is the easiest to implement, but the slowest to converge.
  Works only if all the eigenvalues are real.
  
  @param A The matrix. Not modified.
  @return If it converged or not.