List of solveByTotalPivotSearch() Examples

Examples of solveByTotalPivotSearch()

de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem.solveByTotalPivotSearch()
Solves this linear equation system by total pivot search. "Total pivot search" takes as pivot element the element in the current column having the biggest value. If we have:
( a_11 ... a_1n ) ( 0 ... a_2n ) ( 0 ... a_ii ... a_in ) ( 0 ... a_(i+1)i ... a_(i+1)n ) ( 0 ... a_ni ... a_nn ) Then we search for x,y in {i,...n}, so that |a_xy| > |a_ij|

Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem.solveByTotalPivotSearch()

   *         compatible with values initialized during normalization
   */
  public LinearEquationSystem getNormalizedLinearEquationSystem(Normalization<?> normalization) throws NonNumericFeaturesException {
    if(normalization != null) {
      LinearEquationSystem lq = normalization.transform(linearEquationSystem);
      lq.solveByTotalPivotSearch();
      return lq;
    }
    else {
      return linearEquationSystem;
    }

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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem.solveByTotalPivotSearch()

    // for (double d : beta)
    // System.out.print(d + " ");
    // System.out.println();
    // Solve the equation system (Gauss-Jordan)
    LinearEquationSystem ls = new LinearEquationSystem(covmat, beta);
    ls.solveByTotalPivotSearch();
    // update covmat with the inverse
    covmat = ls.getCoefficents();
    // and deltaparams with the solution vector
    deltaparams = ls.getRHS();
    // deltaparams = beta;

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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem.solveByTotalPivotSearch()

      double[][] we = transposedWeakEigenvectors.getArrayRef();
      double[] b = B.getArrayRef();
      System.arraycopy(we, 0, a, 0, transposedWeakEigenvectors.getRowDimensionality());


      LinearEquationSystem lq = new LinearEquationSystem(a, b);
      lq.solveByTotalPivotSearch();


      sol = new CorrelationAnalysisSolution<V>(lq, db, strongEigenvectors, pcares.getWeakEigenvectors(), pcares.similarityMatrix(), centroid);


      if(logger.isDebuggingFine()) {
        StringBuilder log = new StringBuilder();

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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem.solveByTotalPivotSearch()

   *         compatible with values initialized during normalization
   */
  public LinearEquationSystem getNormalizedLinearEquationSystem(Normalization<?> normalization) throws NonNumericFeaturesException {
    if(normalization != null) {
      LinearEquationSystem lq = normalization.transform(linearEquationSystem);
      lq.solveByTotalPivotSearch();
      return lq;
    }
    else {
      return linearEquationSystem;
    }

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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem.solveByTotalPivotSearch()

    // for (double d : beta)
    // System.out.print(d + " ");
    // System.out.println();
    // Solve the equation system (Gauss-Jordan)
    LinearEquationSystem ls = new LinearEquationSystem(covmat, beta);
    ls.solveByTotalPivotSearch();
    // update covmat with the inverse
    covmat = ls.getCoefficents();
    // and deltaparams with the solution vector
    deltaparams = ls.getRHS();
    // deltaparams = beta;

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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem.solveByTotalPivotSearch()

      double[][] we = transposedWeakEigenvectors.getArrayRef();
      double[] b = B.getArrayRef();
      System.arraycopy(we, 0, a, 0, transposedWeakEigenvectors.getRowDimensionality());


      LinearEquationSystem lq = new LinearEquationSystem(a, b);
      lq.solveByTotalPivotSearch();


      sol = new CorrelationAnalysisSolution<V>(lq, db, strongEigenvectors, pcares.getWeakEigenvectors(), pcares.similarityMatrix(), centroid);


      if(logger.isDebuggingFine()) {
        StringBuilder log = new StringBuilder();

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