Examples of org.apache.mahout.math.function.Mult

org.apache.mahout.math.function.Mult
Only for performance tuning of compute intensive linear algebraic computations. Constructs functions that return one of
- a * constant
- a / constant
a is variable, constant is fixed, but for performance reasons publicly accessible. Intended to be passed to matrix.assign(function) methods.

    }


    IntArrayList nonZeroIndexes =
        new IntArrayList(); // sparsity
    DoubleMatrix1D LUcolj = LU.viewColumn(0).like();  // blocked column j
    Mult multFunction = Mult.mult(0);


    // Outer loop.
    int CUT_OFF = 10;
    for (int j = 0; j < n; j++) {
      // blocking (make copy of j-th column to localize references)
      LUcolj.assign(LU.viewColumn(j));


      // sparsity detection
      int maxCardinality = m / CUT_OFF; // == heuristic depending on speedup
      LUcolj.getNonZeros(nonZeroIndexes, null, maxCardinality);
      int cardinality = nonZeroIndexes.size();
      boolean sparse = (cardinality < maxCardinality);


      // Apply previous transformations.
      for (int i = 0; i < m; i++) {
        int kmax = Math.min(i, j);
        double s;
        if (sparse) {
          s = LUrows[i].zDotProduct(LUcolj, 0, kmax, nonZeroIndexes);
        } else {
          s = LUrows[i].zDotProduct(LUcolj, 0, kmax);
        }
        double before = LUcolj.getQuick(i);
        double after = before - s;
        LUcolj.setQuick(i, after); // LUcolj is a copy
        LU.setQuick(i, j, after);   // this is the original
        if (sparse) {
          if (before == 0 && after != 0) { // nasty bug fixed!
            int pos = nonZeroIndexes.binarySearch(i);
            pos = -pos - 1;
            nonZeroIndexes.beforeInsert(pos, i);
          }
          if (before != 0 && after == 0) {
            nonZeroIndexes.remove(nonZeroIndexes.binarySearch(i));
          }
        }
      }


      // Find pivot and exchange if necessary.
      int p = j;
      if (p < m) {
        double max = Math.abs(LUcolj.getQuick(p));
        for (int i = j + 1; i < m; i++) {
          double v = Math.abs(LUcolj.getQuick(i));
          if (v > max) {
            p = i;
            max = v;
          }
        }
      }
      if (p != j) {
        LUrows[p].swap(LUrows[j]);
        int k = piv[p];
        piv[p] = piv[j];
        piv[j] = k;
        pivsign = -pivsign;
      }


      // Compute multipliers.
      double jj;
      if (j < m && (jj = LU.getQuick(j, j)) != 0.0) {
        multFunction.setMultiplicator(1 / jj);
        LU.viewColumn(j).viewPart(j + 1, m - (j + 1)).assign(multFunction);
      }


    }
    setLU(LU);

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    for (int k = 0; k < n; k++) {
      Brows[k] = B.viewRow(k);
    }


    // transformations
    Mult div = Mult.div(0);
    PlusMult minusMult = PlusMult.minusMult(0);


    IntArrayList nonZeroIndexes =
        new IntArrayList(); // sparsity
    DoubleMatrix1D Browk = org.apache.mahout.math.matrix.DoubleFactory1D.dense.make(nx); // blocked row k


    // Solve L*Y = B(piv,:)
    int CUT_OFF = 10;
    for (int k = 0; k < n; k++) {
      // blocking (make copy of k-th row to localize references)
      Browk.assign(Brows[k]);


      // sparsity detection
      int maxCardinality = nx / CUT_OFF; // == heuristic depending on speedup
      Browk.getNonZeros(nonZeroIndexes, null, maxCardinality);
      int cardinality = nonZeroIndexes.size();
      boolean sparse = (cardinality < maxCardinality);


      for (int i = k + 1; i < n; i++) {
        //for (int j = 0; j < nx; j++) B[i][j] -= B[k][j]*LU[i][k];
        //for (int j = 0; j < nx; j++) B.set(i,j, B.get(i,j) - B.get(k,j)*LU.get(i,k));


        minusMult.setMultiplicator(-LU.getQuick(i, k));
        if (minusMult.getMultiplicator() != 0) {
          if (sparse) {
            Brows[i].assign(Browk, minusMult, nonZeroIndexes);
          } else {
            Brows[i].assign(Browk, minusMult);
          }
        }
      }
    }


    // Solve U*B = Y;
    for (int k = n - 1; k >= 0; k--) {
      // for (int j = 0; j < nx; j++) B[k][j] /= LU[k][k];
      // for (int j = 0; j < nx; j++) B.set(k,j, B.get(k,j) / LU.get(k,k));
      div.setMultiplicator(1 / LU.getQuick(k, k));
      Brows[k].assign(div);


      // blocking
      if (Browk == null) {
        Browk = org.apache.mahout.math.matrix.DoubleFactory1D.dense.make(B.columns());

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    }


    IntArrayList nonZeroIndexes =
        new IntArrayList(); // sparsity
    DoubleMatrix1D luColj = lu.viewColumn(0).like();  // blocked column j
    Mult multFunction = Mult.mult(0);


    // Outer loop.
    int cutOff = 10;
    for (int j = 0; j < n; j++) {
      // blocking (make copy of j-th column to localize references)
      luColj.assign(lu.viewColumn(j));


      // sparsity detection
      int maxCardinality = m / cutOff; // == heuristic depending on speedup
      luColj.getNonZeros(nonZeroIndexes, null, maxCardinality);
      int cardinality = nonZeroIndexes.size();
      boolean sparse = cardinality < maxCardinality;


      // Apply previous transformations.
      for (int i = 0; i < m; i++) {
        int kmax = Math.min(i, j);
        double s;
        if (sparse) {
          s = luRows[i].zDotProduct(luColj, 0, kmax, nonZeroIndexes);
        } else {
          s = luRows[i].zDotProduct(luColj, 0, kmax);
        }
        double before = luColj.getQuick(i);
        double after = before - s;
        luColj.setQuick(i, after); // LUcolj is a copy
        lu.setQuick(i, j, after);   // this is the original
        if (sparse) {
          if (before == 0 && after != 0) { // nasty bug fixed!
            int pos = nonZeroIndexes.binarySearch(i);
            pos = -pos - 1;
            nonZeroIndexes.beforeInsert(pos, i);
          }
          if (before != 0 && after == 0) {
            nonZeroIndexes.remove(nonZeroIndexes.binarySearch(i));
          }
        }
      }


      // Find pivot and exchange if necessary.
      int p = j;
      if (p < m) {
        double max = Math.abs(luColj.getQuick(p));
        for (int i = j + 1; i < m; i++) {
          double v = Math.abs(luColj.getQuick(i));
          if (v > max) {
            p = i;
            max = v;
          }
        }
      }
      if (p != j) {
        luRows[p].swap(luRows[j]);
        int k = piv[p];
        piv[p] = piv[j];
        piv[j] = k;
        pivsign = -pivsign;
      }


      // Compute multipliers.
      double jj;
      if (j < m && (jj = lu.getQuick(j, j)) != 0.0) {
        multFunction.setMultiplicator(1 / jj);
        lu.viewColumn(j).viewPart(j + 1, m - (j + 1)).assign(multFunction);
      }


    }
    setLU(lu);

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    for (int k = 0; k < n; k++) {
      brows[k] = B.viewRow(k);
    }


    // transformations
    Mult div = Mult.div(0);
    PlusMult minusMult = PlusMult.minusMult(0);


    IntArrayList nonZeroIndexes =
        new IntArrayList(); // sparsity
    DoubleMatrix1D bRowk = org.apache.mahout.math.matrix.DoubleFactory1D.dense.make(nx); // blocked row k


    // Solve L*Y = B(piv,:)
    int cutOff = 10;
    for (int k = 0; k < n; k++) {
      // blocking (make copy of k-th row to localize references)
      bRowk.assign(brows[k]);


      // sparsity detection
      int maxCardinality = nx / cutOff; // == heuristic depending on speedup
      bRowk.getNonZeros(nonZeroIndexes, null, maxCardinality);
      int cardinality = nonZeroIndexes.size();
      boolean sparse = cardinality < maxCardinality;


      for (int i = k + 1; i < n; i++) {
        //for (int j = 0; j < nx; j++) B[i][j] -= B[k][j]*LU[i][k];
        //for (int j = 0; j < nx; j++) B.set(i,j, B.get(i,j) - B.get(k,j)*LU.get(i,k));


        minusMult.setMultiplicator(-lu.getQuick(i, k));
        if (minusMult.getMultiplicator() != 0) {
          if (sparse) {
            brows[i].assign(bRowk, minusMult, nonZeroIndexes);
          } else {
            brows[i].assign(bRowk, minusMult);
          }
        }
      }
    }


    // Solve U*B = Y;
    for (int k = n - 1; k >= 0; k--) {
      // for (int j = 0; j < nx; j++) B[k][j] /= LU[k][k];
      // for (int j = 0; j < nx; j++) B.set(k,j, B.get(k,j) / LU.get(k,k));
      div.setMultiplicator(1 / lu.getQuick(k, k));
      brows[k].assign(div);


      // blocking
      //if (bRowk == null) {
      //  bRowk = org.apache.mahout.math.matrix.DoubleFactory1D.dense.make(B.columns());

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Related Classes of org.apache.mahout.math.function.Mult

org.apache.mahout.math.matrix.linalg.LUDecompositionQuick

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