Package org.apache.mahout.math.random

Examples of org.apache.mahout.math.random.MultiNormal.sample()

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  public void testOrdering() {
    searcher.clear();
    Matrix queries = new DenseMatrix(100, 20);
    MultiNormal gen = new MultiNormal(20);
    for (int i = 0; i < 100; i++) {
      queries.viewRow(i).assign(gen.sample());
    }
    searcher.addAllMatrixSlices(dataPoints);

    for (MatrixSlice query : queries) {
      List<WeightedThing<Vector>> r = searcher.search(query.vector(), 200);
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    List<WeightedVector> data = Lists.newArrayListWithCapacity(K1 + 5000);
    int row = 0;

    MultiNormal g = new MultiNormal(radius, new ConstantVector(0, 10));
    for (int i = 0; i < K1; i++) {
      data.add(new WeightedVector(g.sample(), 1, row++));
    }

    for (int i = 0; i < 5; i++) {
      Vector m = new DenseVector(10);
      m.set(i, 6); // This was originally i == 0 ? 6 : 6 which can't be right
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    for (int i = 0; i < 5; i++) {
      Vector m = new DenseVector(10);
      m.set(i, 6); // This was originally i == 0 ? 6 : 6 which can't be right
      MultiNormal gx = new MultiNormal(radius, m);
      for (int j = 0; j < 1000; j++) {
        data.add(new WeightedVector(gx.sample(), 1, row++));
      }
    }
    return data;
  }
}
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    f.deleteOnExit();

    Matrix m0 = new DenseMatrix(100000, 30);
    MultiNormal gen = new MultiNormal(30);
    for (MatrixSlice row : m0) {
      row.vector().assign(gen.sample());
    }
    FileBasedMatrix.writeMatrix(f, m0);

    FileBasedMatrix m = new FileBasedMatrix(100000, 30);
    m.setData(f, true);
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