NoClassDefFoundException Error in java
<p>code:</p>

<p>package Jama;
import Jama.util.*;
import Jama.Matrix;
import Jama.EigenvalueDecomposition;</p>

<p>public class EigenvalueDecomposition implements java.io.Serializable {</p>

<p>/* ------------------------
   Class variables
 * ------------------------ */</p>

<p>/** Row and column dimension (square matrix).
   @serial matrix dimension.
   */
   private int n;</p>

<p>/** Symmetry flag.
   @serial internal symmetry flag.
   */
   private boolean issymmetric;</p>

<p>/** Arrays for internal storage of eigenvalues.
   @serial internal storage of eigenvalues.
   */
   private double[] d, e;</p>

<p>/** Array for internal storage of eigenvectors.
   @serial internal storage of eigenvectors.
   */
   private double[][] V;</p>

<p>/** Array for internal storage of nonsymmetric Hessenberg form.
   @serial internal storage of nonsymmetric Hessenberg form.
   */
   private double[][] H;</p>

<p>/** Working storage for nonsymmetric algorithm.
   @serial working storage for nonsymmetric algorithm.
   */
   private double[] ort;</p>

<p>/* ------------------------
   Private Methods
 * ------------------------ */</p>

<p>// Symmetric Householder reduction to tridiagonal form.</p>

<p>private void tred2 () {</p>

<p>//  This is derived from the Algol procedures tred2 by
   //  Bowdler, Martin, Reinsch, and Wilkinson, Handbook for
   //  Auto. Comp., Vol.ii-Linear Algebra, and the corresponding
   //  Fortran subroutine in EISPACK.</p>

<pre><code>  for (int j = 0; j &lt; n; j++) {
     d[j] = V[n-1][j];
  }

  // Householder reduction to tridiagonal form.

  for (int i = n-1; i &gt; 0; i--) {

     // Scale to avoid under/overflow.

     double scale = 0.0;
     double h = 0.0;
     for (int k = 0; k &lt; i; k++) {
        scale = scale + Math.abs(d[k]);
     }
     if (scale == 0.0) {
        e[i] = d[i-1];
        for (int j = 0; j &lt; i; j++) {
           d[j] = V[i-1][j];
           V[i][j] = 0.0;
           V[j][i] = 0.0;
        }
     } else {

        // Generate Householder vector.

        for (int k = 0; k &lt; i; k++) {
           d[k] /= scale;
           h += d[k] * d[k];
        }
        double f = d[i-1];
        double g = Math.sqrt(h);
        if (f &gt; 0) {
           g = -g;
        }
        e[i] = scale * g;
        h = h - f * g;
        d[i-1] = f - g;
        for (int j = 0; j &lt; i; j++) {
           e[j] = 0.0;
        }

        // Apply similarity transformation to remaining columns.

        for (int j = 0; j &lt; i; j++) {
           f = d[j];
           V[j][i] = f;
           g = e[j] + V[j][j] * f;
           for (int k = j+1; k &lt;= i-1; k++) {
              g += V[k][j] * d[k];
              e[k] += V[k][j] * f;
           }
           e[j] = g;
        }
        f = 0.0;
        for (int j = 0; j &lt; i; j++) {
           e[j] /= h;
           f += e[j] * d[j];
        }
        double hh = f / (h + h);
        for (int j = 0; j &lt; i; j++) {
           e[j] -= hh * d[j];
        }
        for (int j = 0; j &lt; i; j++) {
           f = d[j];
           g = e[j];
           for (int k = j; k &lt;= i-1; k++) {
              V[k][j] -= (f * e[k] + g * d[k]);
           }
           d[j] = V[i-1][j];
           V[i][j] = 0.0;
        }
     }
     d[i] = h;
  }

  // Accumulate transformations.

  for (int i = 0; i &lt; n-1; i++) {
     V[n-1][i] = V[i][i];
     V[i][i] = 1.0;
     double h = d[i+1];
     if (h != 0.0) {
        for (int k = 0; k &lt;= i; k++) {
           d[k] = V[k][i+1] / h;
        }
        for (int j = 0; j &lt;= i; j++) {
           double g = 0.0;
           for (int k = 0; k &lt;= i; k++) {
              g += V[k][i+1] * V[k][j];
           }
           for (int k = 0; k &lt;= i; k++) {
              V[k][j] -= g * d[k];
           }
        }
     }
     for (int k = 0; k &lt;= i; k++) {
        V[k][i+1] = 0.0;
     }
  }
  for (int j = 0; j &lt; n; j++) {
     d[j] = V[n-1][j];
     V[n-1][j] = 0.0;
  }
  V[n-1][n-1] = 1.0;
  e[0] = 0.0;
</code></pre>

<p>} </p>

<p>// Symmetric tridiagonal QL algorithm.</p>

<p>private void tql2 () {</p>

<p>//  This is derived from the Algol procedures tql2, by
   //  Bowdler, Martin, Reinsch, and Wilkinson, Handbook for
   //  Auto. Comp., Vol.ii-Linear Algebra, and the corresponding
   //  Fortran subroutine in EISPACK.</p>

<pre><code>  for (int i = 1; i &lt; n; i++) {
     e[i-1] = e[i];
  }
  e[n-1] = 0.0;

  double f = 0.0;
  double tst1 = 0.0;
  double eps = Math.pow(2.0,-52.0);
  for (int l = 0; l &lt; n; l++) {

     // Find small subdiagonal element

     tst1 = Math.max(tst1,Math.abs(d[l]) + Math.abs(e[l]));
     int m = l;
     while (m &lt; n) {
        if (Math.abs(e[m]) &lt;= eps*tst1) {
           break;
        }
        m++;
     }

     // If m == l, d[l] is an eigenvalue,
     // otherwise, iterate.

     if (m &gt; l) {
        int iter = 0;
        do {
           iter = iter + 1;  // (Could check iteration count here.)

           // Compute implicit shift

           double g = d[l];
           double p = (d[l+1] - g) / (2.0 * e[l]);
           double r = Maths.hypot(p,1.0);
           if (p &lt; 0) {
              r = -r;
           }
           d[l] = e[l] / (p + r);
           d[l+1] = e[l] * (p + r);
           double dl1 = d[l+1];
           double h = g - d[l];
           for (int i = l+2; i &lt; n; i++) {
              d[i] -= h;
           }
           f = f + h;

           // Implicit QL transformation.

           p = d[m];
           double c = 1.0;
           double c2 = c;
           double c3 = c;
           double el1 = e[l+1];
           double s = 0.0;
           double s2 = 0.0;
           for (int i = m-1; i &gt;= l; i--) {
              c3 = c2;
              c2 = c;
              s2 = s;
              g = c * e[i];
              h = c * p;
              r = Maths.hypot(p,e[i]);
              e[i+1] = s * r;
              s = e[i] / r;
              c = p / r;
              p = c * d[i] - s * g;
              d[i+1] = h + s * (c * g + s * d[i]);

              // Accumulate transformation.

              for (int k = 0; k &lt; n; k++) {
                 h = V[k][i+1];
                 V[k][i+1] = s * V[k][i] + c * h;
                 V[k][i] = c * V[k][i] - s * h;
              }
           }
           p = -s * s2 * c3 * el1 * e[l] / dl1;
           e[l] = s * p;
           d[l] = c * p;

           // Check for convergence.

        } while (Math.abs(e[l]) &gt; eps*tst1);
     }
     d[l] = d[l] + f;
     e[l] = 0.0;
  }

  // Sort eigenvalues and corresponding vectors.

  for (int i = 0; i &lt; n-1; i++) {
     int k = i;
     double p = d[i];
     for (int j = i+1; j &lt; n; j++) {
        if (d[j] &lt; p) {
           k = j;
           p = d[j];
        }
     }
     if (k != i) {
        d[k] = d[i];
        d[i] = p;
        for (int j = 0; j &lt; n; j++) {
           p = V[j][i];
           V[j][i] = V[j][k];
           V[j][k] = p;
        }
     }
  }
</code></pre>

<p>}</p>

<p>// Nonsymmetric reduction to Hessenberg form.</p>

<p>private void orthes () {</p>

<pre><code>  //  This is derived from the Algol procedures orthes and ortran,
  //  by Martin and Wilkinson, Handbook for Auto. Comp.,
  //  Vol.ii-Linear Algebra, and the corresponding
  //  Fortran subroutines in EISPACK.

  int low = 0;
  int high = n-1;

  for (int m = low+1; m &lt;= high-1; m++) {

     // Scale column.

     double scale = 0.0;
     for (int i = m; i &lt;= high; i++) {
        scale = scale + Math.abs(H[i][m-1]);
     }
     if (scale != 0.0) {

        // Compute Householder transformation.

        double h = 0.0;
        for (int i = high; i &gt;= m; i--) {
           ort[i] = H[i][m-1]/scale;
           h += ort[i] * ort[i];
        }
        double g = Math.sqrt(h);
        if (ort[m] &gt; 0) {
           g = -g;
        }
        h = h - ort[m] * g;
        ort[m] = ort[m] - g;

        // Apply Householder similarity transformation
        // H = (I-u*u'/h)*H*(I-u*u')/h)

        for (int j = m; j &lt; n; j++) {
           double f = 0.0;
           for (int i = high; i &gt;= m; i--) {
              f += ort[i]*H[i][j];
           }
           f = f/h;
           for (int i = m; i &lt;= high; i++) {
              H[i][j] -= f*ort[i];
           }
       }

       for (int i = 0; i &lt;= high; i++) {
           double f = 0.0;
           for (int j = high; j &gt;= m; j--) {
              f += ort[j]*H[i][j];
           }
           f = f/h;
           for (int j = m; j &lt;= high; j++) {
              H[i][j] -= f*ort[j];
           }
        }
        ort[m] = scale*ort[m];
        H[m][m-1] = scale*g;
     }
  }

  // Accumulate transformations (Algol's ortran).

  for (int i = 0; i &lt; n; i++) {
     for (int j = 0; j &lt; n; j++) {
        V[i][j] = (i == j ? 1.0 : 0.0);
     }
  }

  for (int m = high-1; m &gt;= low+1; m--) {
     if (H[m][m-1] != 0.0) {
        for (int i = m+1; i &lt;= high; i++) {
           ort[i] = H[i][m-1];
        }
        for (int j = m; j &lt;= high; j++) {
           double g = 0.0;
           for (int i = m; i &lt;= high; i++) {
              g += ort[i] * V[i][j];
           }
           // Double division avoids possible underflow
           g = (g / ort[m]) / H[m][m-1];
           for (int i = m; i &lt;= high; i++) {
              V[i][j] += g * ort[i];
           }
        }
     }
  }
</code></pre>

<p>}</p>

<p>// Complex scalar division.</p>

<p>private transient double cdivr, cdivi;
   private void cdiv(double xr, double xi, double yr, double yi) {
      double r,d;
      if (Math.abs(yr) > Math.abs(yi)) {
         r = yi/yr;
         d = yr + r*yi;
         cdivr = (xr + r*xi)/d;
         cdivi = (xi - r*xr)/d;
      } else {
         r = yr/yi;
         d = yi + r*yr;
         cdivr = (r*xr + xi)/d;
         cdivi = (r*xi - xr)/d;
      }
   }</p>

<p>// Nonsymmetric reduction from Hessenberg to real Schur form.</p>

<p>private void hqr2 () {</p>

<pre><code>  //  This is derived from the Algol procedure hqr2,
  //  by Martin and Wilkinson, Handbook for Auto. Comp.,
  //  Vol.ii-Linear Algebra, and the corresponding
  //  Fortran subroutine in EISPACK.

  // Initialize

  int nn = this.n;
  int n = nn-1;
  int low = 0;
  int high = nn-1;
  double eps = Math.pow(2.0,-52.0);
  double exshift = 0.0;
  double p=0,q=0,r=0,s=0,z=0,t,w,x,y;

  // Store roots isolated by balanc and compute matrix norm

  double norm = 0.0;
  for (int i = 0; i &lt; nn; i++) {
     if (i &lt; low | i &gt; high) {
        d[i] = H[i][i];
        e[i] = 0.0;
     }
     for (int j = Math.max(i-1,0); j &lt; nn; j++) {
        norm = norm + Math.abs(H[i][j]);
     }
  }

  // Outer loop over eigenvalue index

  int iter = 0;
  while (n &gt;= low) {

     // Look for single small sub-diagonal element

     int l = n;
     while (l &gt; low) {
        s = Math.abs(H[l-1][l-1]) + Math.abs(H[l][l]);
        if (s == 0.0) {
           s = norm;
        }
        if (Math.abs(H[l][l-1]) &lt; eps * s) {
           break;
        }
        l--;
     }

     // Check for convergence
     // One root found

     if (l == n) {
        H[n][n] = H[n][n] + exshift;
        d[n] = H[n][n];
        e[n] = 0.0;
        n--;
        iter = 0;

     // Two roots found

     } else if (l == n-1) {
        w = H[n][n-1] * H[n-1][n];
        p = (H[n-1][n-1] - H[n][n]) / 2.0;
        q = p * p + w;
        z = Math.sqrt(Math.abs(q));
        H[n][n] = H[n][n] + exshift;
        H[n-1][n-1] = H[n-1][n-1] + exshift;
        x = H[n][n];

        // Real pair

        if (q &gt;= 0) {
           if (p &gt;= 0) {
              z = p + z;
           } else {
              z = p - z;
           }
           d[n-1] = x + z;
           d[n] = d[n-1];
           if (z != 0.0) {
              d[n] = x - w / z;
           }
           e[n-1] = 0.0;
           e[n] = 0.0;
           x = H[n][n-1];
           s = Math.abs(x) + Math.abs(z);
           p = x / s;
           q = z / s;
           r = Math.sqrt(p * p+q * q);
           p = p / r;
           q = q / r;

           // Row modification

           for (int j = n-1; j &lt; nn; j++) {
              z = H[n-1][j];
              H[n-1][j] = q * z + p * H[n][j];
              H[n][j] = q * H[n][j] - p * z;
           }

           // Column modification

           for (int i = 0; i &lt;= n; i++) {
              z = H[i][n-1];
              H[i][n-1] = q * z + p * H[i][n];
              H[i][n] = q * H[i][n] - p * z;
           }

           // Accumulate transformations

           for (int i = low; i &lt;= high; i++) {
              z = V[i][n-1];
              V[i][n-1] = q * z + p * V[i][n];
              V[i][n] = q * V[i][n] - p * z;
           }

        // Complex pair

        } else {
           d[n-1] = x + p;
           d[n] = x + p;
           e[n-1] = z;
           e[n] = -z;
        }
        n = n - 2;
        iter = 0;

     // No convergence yet

     } else {

        // Form shift

        x = H[n][n];
        y = 0.0;
        w = 0.0;
        if (l &lt; n) {
           y = H[n-1][n-1];
           w = H[n][n-1] * H[n-1][n];
        }

        // Wilkinson's original ad hoc shift

        if (iter == 10) {
           exshift += x;
           for (int i = low; i &lt;= n; i++) {
              H[i][i] -= x;
           }
           s = Math.abs(H[n][n-1]) + Math.abs(H[n-1][n-2]);
           x = y = 0.75 * s;
           w = -0.4375 * s * s;
        }

        // MATLAB's new ad hoc shift

        if (iter == 30) {
            s = (y - x) / 2.0;
            s = s * s + w;
            if (s &gt; 0) {
                s = Math.sqrt(s);
                if (y &lt; x) {
                   s = -s;
                }
                s = x - w / ((y - x) / 2.0 + s);
                for (int i = low; i &lt;= n; i++) {
                   H[i][i] -= s;
                }
                exshift += s;
                x = y = w = 0.964;
            }
        }

        iter = iter + 1;   // (Could check iteration count here.)

        // Look for two consecutive small sub-diagonal elements

        int m = n-2;
        while (m &gt;= l) {
           z = H[m][m];
           r = x - z;
           s = y - z;
           p = (r * s - w) / H[m+1][m] + H[m][m+1];
           q = H[m+1][m+1] - z - r - s;
           r = H[m+2][m+1];
           s = Math.abs(p) + Math.abs(q) + Math.abs(r);
           p = p / s;
           q = q / s;
           r = r / s;
           if (m == l) {
              break;
           }
           if (Math.abs(H[m][m-1]) * (Math.abs(q) + Math.abs(r)) &lt;
              eps * (Math.abs(p) * (Math.abs(H[m-1][m-1]) + Math.abs(z) +
              Math.abs(H[m+1][m+1])))) {
                 break;
           }
           m--;
        }

        for (int i = m+2; i &lt;= n; i++) {
           H[i][i-2] = 0.0;
           if (i &gt; m+2) {
              H[i][i-3] = 0.0;
           }
        }

        // Double QR step involving rows l:n and columns m:n

        for (int k = m; k &lt;= n-1; k++) {
           boolean notlast = (k != n-1);
           if (k != m) {
              p = H[k][k-1];
              q = H[k+1][k-1];
              r = (notlast ? H[k+2][k-1] : 0.0);
              x = Math.abs(p) + Math.abs(q) + Math.abs(r);
              if (x != 0.0) {
                 p = p / x;
                 q = q / x;
                 r = r / x;
              }
           }
           if (x == 0.0) {
              break;
           }
           s = Math.sqrt(p * p + q * q + r * r);
           if (p &lt; 0) {
              s = -s;
           }
           if (s != 0) {
              if (k != m) {
                 H[k][k-1] = -s * x;
              } else if (l != m) {
                 H[k][k-1] = -H[k][k-1];
              }
              p = p + s;
              x = p / s;
              y = q / s;
              z = r / s;
              q = q / p;
              r = r / p;

              // Row modification

              for (int j = k; j &lt; nn; j++) {
                 p = H[k][j] + q * H[k+1][j];
                 if (notlast) {
                    p = p + r * H[k+2][j];
                    H[k+2][j] = H[k+2][j] - p * z;
                 }
                 H[k][j] = H[k][j] - p * x;
                 H[k+1][j] = H[k+1][j] - p * y;
              }

              // Column modification

              for (int i = 0; i &lt;= Math.min(n,k+3); i++) {
                 p = x * H[i][k] + y * H[i][k+1];
                 if (notlast) {
                    p = p + z * H[i][k+2];
                    H[i][k+2] = H[i][k+2] - p * r;
                 }
                 H[i][k] = H[i][k] - p;
                 H[i][k+1] = H[i][k+1] - p * q;
              }

              // Accumulate transformations

              for (int i = low; i &lt;= high; i++) {
                 p = x * V[i][k] + y * V[i][k+1];
                 if (notlast) {
                    p = p + z * V[i][k+2];
                    V[i][k+2] = V[i][k+2] - p * r;
                 }
                 V[i][k] = V[i][k] - p;
                 V[i][k+1] = V[i][k+1] - p * q;
              }
           }  // (s != 0)
        }  // k loop
     }  // check convergence
  }  // while (n &gt;= low)

  // Backsubstitute to find vectors of upper triangular form

  if (norm == 0.0) {
     return;
  }

  for (n = nn-1; n &gt;= 0; n--) {
     p = d[n];
     q = e[n];

     // Real vector

     if (q == 0) {
        int l = n;
        H[n][n] = 1.0;
        for (int i = n-1; i &gt;= 0; i--) {
           w = H[i][i] - p;
           r = 0.0;
           for (int j = l; j &lt;= n; j++) {
              r = r + H[i][j] * H[j][n];
           }
           if (e[i] &lt; 0.0) {
              z = w;
              s = r;
           } else {
              l = i;
              if (e[i] == 0.0) {
                 if (w != 0.0) {
                    H[i][n] = -r / w;
                 } else {
                    H[i][n] = -r / (eps * norm);
                 }

              // Solve real equations

              } else {
                 x = H[i][i+1];
                 y = H[i+1][i];
                 q = (d[i] - p) * (d[i] - p) + e[i] * e[i];
                 t = (x * s - z * r) / q;
                 H[i][n] = t;
                 if (Math.abs(x) &gt; Math.abs(z)) {
                    H[i+1][n] = (-r - w * t) / x;
                 } else {
                    H[i+1][n] = (-s - y * t) / z;
                 }
              }

              // Overflow control

              t = Math.abs(H[i][n]);
              if ((eps * t) * t &gt; 1) {
                 for (int j = i; j &lt;= n; j++) {
                    H[j][n] = H[j][n] / t;
                 }
              }
           }
        }

     // Complex vector

     } else if (q &lt; 0) {
        int l = n-1;

        // Last vector component imaginary so matrix is triangular

        if (Math.abs(H[n][n-1]) &gt; Math.abs(H[n-1][n])) {
           H[n-1][n-1] = q / H[n][n-1];
           H[n-1][n] = -(H[n][n] - p) / H[n][n-1];
        } else {
           cdiv(0.0,-H[n-1][n],H[n-1][n-1]-p,q);
           H[n-1][n-1] = cdivr;
           H[n-1][n] = cdivi;
        }
        H[n][n-1] = 0.0;
        H[n][n] = 1.0;
        for (int i = n-2; i &gt;= 0; i--) {
           double ra,sa,vr,vi;
           ra = 0.0;
           sa = 0.0;
           for (int j = l; j &lt;= n; j++) {
              ra = ra + H[i][j] * H[j][n-1];
              sa = sa + H[i][j] * H[j][n];
           }
           w = H[i][i] - p;

           if (e[i] &lt; 0.0) {
              z = w;
              r = ra;
              s = sa;
           } else {
              l = i;
              if (e[i] == 0) {
                 cdiv(-ra,-sa,w,q);
                 H[i][n-1] = cdivr;
                 H[i][n] = cdivi;
              } else {

                 // Solve complex equations

                 x = H[i][i+1];
                 y = H[i+1][i];
                 vr = (d[i] - p) * (d[i] - p) + e[i] * e[i] - q * q;
                 vi = (d[i] - p) * 2.0 * q;
                 if (vr == 0.0 &amp; vi == 0.0) {
                    vr = eps * norm * (Math.abs(w) + Math.abs(q) +
                    Math.abs(x) + Math.abs(y) + Math.abs(z));
                 }
                 cdiv(x*r-z*ra+q*sa,x*s-z*sa-q*ra,vr,vi);
                 H[i][n-1] = cdivr;
                 H[i][n] = cdivi;
                 if (Math.abs(x) &gt; (Math.abs(z) + Math.abs(q))) {
                    H[i+1][n-1] = (-ra - w * H[i][n-1] + q * H[i][n]) / x;
                    H[i+1][n] = (-sa - w * H[i][n] - q * H[i][n-1]) / x;
                 } else {
                    cdiv(-r-y*H[i][n-1],-s-y*H[i][n],z,q);
                    H[i+1][n-1] = cdivr;
                    H[i+1][n] = cdivi;
                 }
              }

              // Overflow control

              t = Math.max(Math.abs(H[i][n-1]),Math.abs(H[i][n]));
              if ((eps * t) * t &gt; 1) {
                 for (int j = i; j &lt;= n; j++) {
                    H[j][n-1] = H[j][n-1] / t;
                    H[j][n] = H[j][n] / t;
                 }
              }
           }
        }
     }
  }

  // Vectors of isolated roots

  for (int i = 0; i &lt; nn; i++) {
     if (i &lt; low | i &gt; high) {
        for (int j = i; j &lt; nn; j++) {
           V[i][j] = H[i][j];
        }
     }
  }

  // Back transformation to get eigenvectors of original matrix

  for (int j = nn-1; j &gt;= low; j--) {
     for (int i = low; i &lt;= high; i++) {
        z = 0.0;
        for (int k = low; k &lt;= Math.min(j,high); k++) {
           z = z + V[i][k] * H[k][j];
        }
        V[i][j] = z;
     }
  }
</code></pre>

<p>}</p>

<p>/* ------------------------
   Constructor
 * ------------------------ */</p>

<p>/** Check for symmetry, then construct the eigenvalue decomposition
   @param A    Square matrix
   @return     Structure to access D and V.
   */</p>

<p>public EigenvalueDecomposition (Matrix Arg) {
      double[][] A = Arg.getArray();
      n = Arg.getColumnDimension();
      V = new double[n][n];
      d = new double[n];
      e = new double[n];</p>

<pre><code>  issymmetric = true;
  for (int j = 0; (j &lt; n) &amp; issymmetric; j++) {
     for (int i = 0; (i &lt; n) &amp; issymmetric; i++) {
        issymmetric = (A[i][j] == A[j][i]);
     }
  }

  if (issymmetric) {
     for (int i = 0; i &lt; n; i++) {
        for (int j = 0; j &lt; n; j++) {
           V[i][j] = A[i][j];
        }
     }

     // Tridiagonalize.
     tred2();

     // Diagonalize.
     tql2();

  } else {
     H = new double[n][n];
     ort = new double[n];

     for (int j = 0; j &lt; n; j++) {
        for (int i = 0; i &lt; n; i++) {
           H[i][j] = A[i][j];
        }
     }

     // Reduce to Hessenberg form.
     orthes();

     // Reduce Hessenberg to real Schur form.
     hqr2();
  }
</code></pre>

<p>}</p>

<p>/* ------------------------
   Public Methods
 * ------------------------ */</p>

<p>/** Return the eigenvector matrix
   @return     V
   */</p>

<p>public Matrix getV () {
      return new Matrix(V,n,n);
   }</p>

<p>/** Return the real parts of the eigenvalues
   @return     real(diag(D))
   */</p>

<p>public double[] getRealEigenvalues () {
      return d;
   }</p>

<p>/** Return the imaginary parts of the eigenvalues
   @return     imag(diag(D))
   */</p>

<p>public double[] getImagEigenvalues () {
      return e;
   }</p>

<p>/** Return the block diagonal eigenvalue matrix
   @return     D
   */</p>

<p>public Matrix getD () {
      Matrix X = new Matrix(n,n);
      double[][] D = X.getArray();
      for (int i = 0; i &lt; n; i++) {
         for (int j = 0; j &lt; n; j++) {
            D[i][j] = 0.0;
         }
         D[i][i] = d[i];
         if (e[i] > 0) {
            D[i][i+1] = e[i];
         } else if (e[i] &lt; 0) {
            D[i][i-1] = e[i];
         }
      }
      return X;
   }
}</p>

<p>this code gives NoClassDefFoundException Error. i dont know where is the actual error is occured in program.pls suggest me proper solution.
thx.</p>
