All Downloads are FREE. Search and download functionalities are using the official Maven repository.

org.carrot2.mahout.math.SingularValueDecomposition Maven / Gradle / Ivy

Go to download

Carrot2 search results clustering framework. Minimal functional subset (core algorithms and infrastructure, no document sources).

There is a newer version: 3.16.3
Show newest version
/* Imported from Mahout. */package org.carrot2.mahout.math;

public class SingularValueDecomposition {
  
  
  private final double[][] u;
  private final double[][] v;
  
  
  private final double[] s;
  
  
  private final int m;
  private final int n;
  
  
  private boolean transpositionNeeded = false;
  
  
  public SingularValueDecomposition(Matrix arg) {
    if (arg.numRows() < arg.numCols()) {
      transpositionNeeded = true;
    }
    
    // Derived from LINPACK code.
    // Initialize.
    double[][] a;
    if (transpositionNeeded) {
      //use the transpose Matrix
      m = arg.numCols();
      n = arg.numRows();
      a = new double[m][n];
      for (int i = 0; i < m; i++) {
        for (int j = 0; j < n; j++) {
          a[i][j] = arg.get(j, i);
        }
      }
    } else {
      m = arg.numRows();
      n = arg.numCols();
      a = new double[m][n];
      for (int i = 0; i < m; i++) {
        for (int j = 0; j < n; j++) {
          a[i][j] = arg.get(i, j);
        }
      }
    }
    
    
    int nu = Math.min(m, n);
    s = new double[Math.min(m + 1, n)];
    u = new double[m][nu];
    v = new double[n][n];
    double[] e = new double[n];
    double[] work = new double[m];
    boolean wantu = true;
    boolean wantv = true;
    
    // Reduce A to bidiagonal form, storing the diagonal elements
    // in s and the super-diagonal elements in e.
    
    int nct = Math.min(m - 1, n);
    int nrt = Math.max(0, Math.min(n - 2, m));
    for (int k = 0; k < Math.max(nct, nrt); k++) {
      if (k < nct) {
        
        // Compute the transformation for the k-th column and
        // place the k-th diagonal in s[k].
        // Compute 2-norm of k-th column without under/overflow.
        s[k] = 0;
        for (int i = k; i < m; i++) {
          s[k] = Algebra.hypot(s[k], a[i][k]);
        }
        if (s[k] != 0.0) {
          if (a[k][k] < 0.0) {
            s[k] = -s[k];
          }
          for (int i = k; i < m; i++) {
            a[i][k] /= s[k];
          }
          a[k][k] += 1.0;
        }
        s[k] = -s[k];
      }
      for (int j = k + 1; j < n; j++) {
        if (k < nct && s[k] != 0.0) {
          
          // Apply the transformation.
          
          double t = 0;
          for (int i = k; i < m; i++) {
            t += a[i][k] * a[i][j];
          }
          t = -t / a[k][k];
          for (int i = k; i < m; i++) {
            a[i][j] += t * a[i][k];
          }
        }
        
        // Place the k-th row of A into e for the
        // subsequent calculation of the row transformation.
        
        e[j] = a[k][j];
      }
      if (wantu && k < nct) {
        
        // Place the transformation in U for subsequent back
        // multiplication.
        
        for (int i = k; i < m; i++) {
          u[i][k] = a[i][k];
        }
      }
      if (k < nrt) {
        
        // Compute the k-th row transformation and place the
        // k-th super-diagonal in e[k].
        // Compute 2-norm without under/overflow.
        e[k] = 0;
        for (int i = k + 1; i < n; i++) {
          e[k] = Algebra.hypot(e[k], e[i]);
        }
        if (e[k] != 0.0) {
          if (e[k + 1] < 0.0) {
            e[k] = -e[k];
          }
          for (int i = k + 1; i < n; i++) {
            e[i] /= e[k];
          }
          e[k + 1] += 1.0;
        }
        e[k] = -e[k];
        if (k + 1 < m && e[k] != 0.0) {
          
          // Apply the transformation.
          
          for (int i = k + 1; i < m; i++) {
            work[i] = 0.0;
          }
          for (int j = k + 1; j < n; j++) {
            for (int i = k + 1; i < m; i++) {
              work[i] += e[j] * a[i][j];
            }
          }
          for (int j = k + 1; j < n; j++) {
            double t = -e[j] / e[k + 1];
            for (int i = k + 1; i < m; i++) {
              a[i][j] += t * work[i];
            }
          }
        }
        if (wantv) {
          
          // Place the transformation in V for subsequent
          // back multiplication.
          
          for (int i = k + 1; i < n; i++) {
            v[i][k] = e[i];
          }
        }
      }
    }
    
    // Set up the final bidiagonal matrix or order p.
    
    int p = Math.min(n, m + 1);
    if (nct < n) {
      s[nct] = a[nct][nct];
    }
    if (m < p) {
      s[p - 1] = 0.0;
    }
    if (nrt + 1 < p) {
      e[nrt] = a[nrt][p - 1];
    }
    e[p - 1] = 0.0;
    
    // If required, generate U.
    
    if (wantu) {
      for (int j = nct; j < nu; j++) {
        for (int i = 0; i < m; i++) {
          u[i][j] = 0.0;
        }
        u[j][j] = 1.0;
      }
      for (int k = nct - 1; k >= 0; k--) {
        if (s[k] != 0.0) {
          for (int j = k + 1; j < nu; j++) {
            double t = 0;
            for (int i = k; i < m; i++) {
              t += u[i][k] * u[i][j];
            }
            t = -t / u[k][k];
            for (int i = k; i < m; i++) {
              u[i][j] += t * u[i][k];
            }
          }
          for (int i = k; i < m; i++) {
            u[i][k] = -u[i][k];
          }
          u[k][k] = 1.0 + u[k][k];
          for (int i = 0; i < k - 1; i++) {
            u[i][k] = 0.0;
          }
        } else {
          for (int i = 0; i < m; i++) {
            u[i][k] = 0.0;
          }
          u[k][k] = 1.0;
        }
      }
    }
    
    // If required, generate V.
    
    if (wantv) {
      for (int k = n - 1; k >= 0; k--) {
        if (k < nrt && e[k] != 0.0) {
          for (int j = k + 1; j < nu; j++) {
            double t = 0;
            for (int i = k + 1; i < n; i++) {
              t += v[i][k] * v[i][j];
            }
            t = -t / v[k + 1][k];
            for (int i = k + 1; i < n; i++) {
              v[i][j] += t * v[i][k];
            }
          }
        }
        for (int i = 0; i < n; i++) {
          v[i][k] = 0.0;
        }
        v[k][k] = 1.0;
      }
    }
    
    // Main iteration loop for the singular values.
    
    int pp = p - 1;
    //int iter = 0;
    double eps = Math.pow(2.0, -52.0);
    while (p > 0) {
      int k;
      
      // Here is where a test for too many iterations would go.
      
      // This section of the program inspects for
      // negligible elements in the s and e arrays.  On
      // completion the variables kase and k are set as follows.
      
      // kase = 1     if s(p) and e[k-1] are negligible and k

= -1; k--) { if (k == -1) { break; } if (Math.abs(e[k]) <= eps * (Math.abs(s[k]) + Math.abs(s[k + 1]))) { e[k] = 0.0; break; } } int kase; if (k == p - 2) { kase = 4; } else { int ks; for (ks = p - 1; ks >= k; ks--) { if (ks == k) { break; } double t = (ks == p ? 0.0 : Math.abs(e[ks])) + (ks == k + 1 ? 0.0 : Math.abs(e[ks - 1])); if (Math.abs(s[ks]) <= eps * t) { s[ks] = 0.0; break; } } if (ks == k) { kase = 3; } else if (ks == p - 1) { kase = 1; } else { kase = 2; k = ks; } } k++; // Perform the task indicated by kase. switch (kase) { // Deflate negligible s(p). case 1: { double f = e[p - 2]; e[p - 2] = 0.0; for (int j = p - 2; j >= k; j--) { double t = Algebra.hypot(s[j], f); double cs = s[j] / t; double sn = f / t; s[j] = t; if (j != k) { f = -sn * e[j - 1]; e[j - 1] = cs * e[j - 1]; } if (wantv) { for (int i = 0; i < n; i++) { t = cs * v[i][j] + sn * v[i][p - 1]; v[i][p - 1] = -sn * v[i][j] + cs * v[i][p - 1]; v[i][j] = t; } } } } break; // Split at negligible s(k). case 2: { double f = e[k - 1]; e[k - 1] = 0.0; for (int j = k; j < p; j++) { double t = Algebra.hypot(s[j], f); double cs = s[j] / t; double sn = f / t; s[j] = t; f = -sn * e[j]; e[j] = cs * e[j]; if (wantu) { for (int i = 0; i < m; i++) { t = cs * u[i][j] + sn * u[i][k - 1]; u[i][k - 1] = -sn * u[i][j] + cs * u[i][k - 1]; u[i][j] = t; } } } } break; // Perform one qr step. case 3: { // Calculate the shift. double scale = Math.max(Math.max(Math.max(Math.max( Math.abs(s[p - 1]), Math.abs(s[p - 2])), Math.abs(e[p - 2])), Math.abs(s[k])), Math.abs(e[k])); double sp = s[p - 1] / scale; double spm1 = s[p - 2] / scale; double epm1 = e[p - 2] / scale; double sk = s[k] / scale; double ek = e[k] / scale; double b = ((spm1 + sp) * (spm1 - sp) + epm1 * epm1) / 2.0; double c = sp * epm1 * sp * epm1; double shift = 0.0; if (b != 0.0 || c != 0.0) { shift = Math.sqrt(b * b + c); if (b < 0.0) { shift = -shift; } shift = c / (b + shift); } double f = (sk + sp) * (sk - sp) + shift; double g = sk * ek; // Chase zeros. for (int j = k; j < p - 1; j++) { double t = Algebra.hypot(f, g); double cs = f / t; double sn = g / t; if (j != k) { e[j - 1] = t; } f = cs * s[j] + sn * e[j]; e[j] = cs * e[j] - sn * s[j]; g = sn * s[j + 1]; s[j + 1] = cs * s[j + 1]; if (wantv) { for (int i = 0; i < n; i++) { t = cs * v[i][j] + sn * v[i][j + 1]; v[i][j + 1] = -sn * v[i][j] + cs * v[i][j + 1]; v[i][j] = t; } } t = Algebra.hypot(f, g); cs = f / t; sn = g / t; s[j] = t; f = cs * e[j] + sn * s[j + 1]; s[j + 1] = -sn * e[j] + cs * s[j + 1]; g = sn * e[j + 1]; e[j + 1] = cs * e[j + 1]; if (wantu && j < m - 1) { for (int i = 0; i < m; i++) { t = cs * u[i][j] + sn * u[i][j + 1]; u[i][j + 1] = -sn * u[i][j] + cs * u[i][j + 1]; u[i][j] = t; } } } e[p - 2] = f; //iter += 1; } break; // Convergence. case 4: { // Make the singular values positive. if (s[k] <= 0.0) { s[k] = s[k] < 0.0 ? -s[k] : 0.0; if (wantv) { for (int i = 0; i <= pp; i++) { v[i][k] = -v[i][k]; } } } // Order the singular values. while (k < pp) { if (s[k] >= s[k + 1]) { break; } double t = s[k]; s[k] = s[k + 1]; s[k + 1] = t; if (wantv && k < n - 1) { for (int i = 0; i < n; i++) { t = v[i][k + 1]; v[i][k + 1] = v[i][k]; v[i][k] = t; } } if (wantu && k < m - 1) { for (int i = 0; i < m; i++) { t = u[i][k + 1]; u[i][k + 1] = u[i][k]; u[i][k] = t; } } k++; } //iter = 0; p--; } break; default: throw new IllegalStateException(); } } } public double cond() { return s[0] / s[Math.min(m, n) - 1]; } public Matrix getS() { double[][] s = new double[n][n]; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { s[i][j] = 0.0; } s[i][i] = this.s[i]; } return new DenseMatrix(s); } public double[] getSingularValues() { return s; } public Matrix getU() { if (transpositionNeeded) { //case numRows() < numCols() return new DenseMatrix(v); } else { int numCols = Math.min(m + 1, n); Matrix r = new DenseMatrix(m, numCols); for (int i = 0; i < m; i++) { for (int j = 0; j < numCols; j++) { r.set(i, j, u[i][j]); } } return r; } } public Matrix getV() { if (transpositionNeeded) { //case numRows() < numCols() int numCols = Math.min(m + 1, n); Matrix r = new DenseMatrix(m, numCols); for (int i = 0; i < m; i++) { for (int j = 0; j < numCols; j++) { r.set(i, j, u[i][j]); } } return r; } else { return new DenseMatrix(v); } } public double norm2() { return s[0]; } public int rank() { double eps = Math.pow(2.0, -52.0); double tol = Math.max(m, n) * s[0] * eps; int r = 0; for (double value : s) { if (value > tol) { r++; } } return r; } Matrix getCovariance(double minSingularValue) { Matrix j = new DenseMatrix(s.length,s.length); Matrix vMat = new DenseMatrix(this.v); for (int i = 0; i < s.length; i++) { j.set(i, i, s[i] >= minSingularValue ? 1 / (s[i] * s[i]) : 0.0); } return vMat.times(j).times(vMat.transpose()); } @Override public String toString() { StringBuilder buf = new StringBuilder(); buf.append("---------------------------------------------------------------------\n"); buf.append("SingularValueDecomposition(A) --> cond(A), rank(A), norm2(A), U, S, V\n"); buf.append("---------------------------------------------------------------------\n"); buf.append("cond = "); String unknown = "Illegal operation or error: "; try { buf.append(String.valueOf(this.cond())); } catch (IllegalArgumentException exc) { buf.append(unknown).append(exc.getMessage()); } buf.append("\nrank = "); try { buf.append(String.valueOf(this.rank())); } catch (IllegalArgumentException exc) { buf.append(unknown).append(exc.getMessage()); } buf.append("\nnorm2 = "); try { buf.append(String.valueOf(this.norm2())); } catch (IllegalArgumentException exc) { buf.append(unknown).append(exc.getMessage()); } buf.append("\n\nU = "); try { buf.append(String.valueOf(this.getU())); } catch (IllegalArgumentException exc) { buf.append(unknown).append(exc.getMessage()); } buf.append("\n\nS = "); try { buf.append(String.valueOf(this.getS())); } catch (IllegalArgumentException exc) { buf.append(unknown).append(exc.getMessage()); } buf.append("\n\nV = "); try { buf.append(String.valueOf(this.getV())); } catch (IllegalArgumentException exc) { buf.append(unknown).append(exc.getMessage()); } return buf.toString(); } }





© 2015 - 2024 Weber Informatics LLC | Privacy Policy