Package org.apache.mahout.math

Examples of org.apache.mahout.math.Matrix.numRows()

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    Matrix similarityMatrix = MathHelper.readMatrix(conf, new Path(outputDir.getAbsolutePath(), "part-r-00000"), 3, 3);

    assertNotNull(similarityMatrix);
    assertEquals(3, similarityMatrix.numCols());
    assertEquals(3, similarityMatrix.numRows());

    assertEquals(0.0, similarityMatrix.get(0, 0), EPSILON);
    assertEquals(0.5, similarityMatrix.get(0, 1), EPSILON);
    assertEquals(0.0, similarityMatrix.get(0, 2), EPSILON);
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    Matrix similarityMatrix = MathHelper.readMatrix(conf, new Path(outputDir.getAbsolutePath(), "part-r-00000"), 3, 3);

    assertNotNull(similarityMatrix);
    assertEquals(3, similarityMatrix.numCols());
    assertEquals(3, similarityMatrix.numRows());

    assertEquals(0.0, similarityMatrix.get(0, 0), EPSILON);
    assertEquals(0.5, similarityMatrix.get(0, 1), EPSILON);
    assertEquals(0.0, similarityMatrix.get(0, 2), EPSILON);
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    DistributedRowMatrix dm =
        randomDistributedMatrix(100, 90, 50, 20, 1.0, false);
    dm.setConf(getConfiguration());

    Vector expected = new DenseVector(50);
    for (int i = 0; i < m.numRows(); i++) {
      expected.assign(m.viewRow(i), Functions.PLUS);
    }
    expected.assign(Functions.DIV, m.numRows());
    Vector actual = dm.columnMeans("DenseVector");
    assertEquals(0.0, expected.getDistanceSquared(actual), EPSILON);
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    Vector expected = new DenseVector(50);
    for (int i = 0; i < m.numRows(); i++) {
      expected.assign(m.viewRow(i), Functions.PLUS);
    }
    expected.assign(Functions.DIV, m.numRows());
    Vector actual = dm.columnMeans("DenseVector");
    assertEquals(0.0, expected.getDistanceSquared(actual), EPSILON);
  }

  @Test
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    DistributedRowMatrix dm =
        randomDistributedMatrix(100, 90, 0, 0, 1.0, false);
    dm.setConf(getConfiguration());

    Vector expected = new DenseVector(0);
    for (int i = 0; i < m.numRows(); i++) {
      expected.assign(m.viewRow(i), Functions.PLUS);
    }
    expected.assign(Functions.DIV, m.numRows());
    Vector actual = dm.columnMeans();
    assertEquals(0.0, expected.getDistanceSquared(actual), EPSILON);
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    Vector expected = new DenseVector(0);
    for (int i = 0; i < m.numRows(); i++) {
      expected.assign(m.viewRow(i), Functions.PLUS);
    }
    expected.assign(Functions.DIV, m.numRows());
    Vector actual = dm.columnMeans();
    assertEquals(0.0, expected.getDistanceSquared(actual), EPSILON);
  }

  @Test
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        IntWritable.class, VectorWritable.class);
    try {
      IntWritable key = new IntWritable();
      VectorWritable value = new VectorWritable();
     
      for (int row = 0; row < sData.numRows(); row++) {
        key.set(row);
        value.set(sData.viewRow(row));
        writer.append(key, value);
      }
    } finally {
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    Matrix similarityMatrix = MathHelper.readMatrix(conf, new Path(outputDir.getAbsolutePath(), "part-r-00000"), 3, 3);

    assertNotNull(similarityMatrix);
    assertEquals(3, similarityMatrix.numCols());
    assertEquals(3, similarityMatrix.numRows());

    assertEquals(1.0, similarityMatrix.get(0, 0), EPSILON);
    assertEquals(1.0, similarityMatrix.get(1, 1), EPSILON);
    assertEquals(1.0, similarityMatrix.get(2, 2), EPSILON);
    assertEquals(0.0, similarityMatrix.get(2, 0), EPSILON);
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    Matrix similarityMatrix = MathHelper.readMatrix(conf, new Path(outputDir.getAbsolutePath(), "part-r-00000"), 3, 3);

    assertNotNull(similarityMatrix);
    assertEquals(3, similarityMatrix.numCols());
    assertEquals(3, similarityMatrix.numRows());

    assertEquals(0.0, similarityMatrix.get(0, 0), EPSILON);
    assertEquals(0.5, similarityMatrix.get(0, 1), EPSILON);
    assertEquals(0.0, similarityMatrix.get(0, 2), EPSILON);
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    Matrix similarityMatrix = MathHelper.readMatrix(conf, new Path(outputDir.getAbsolutePath(), "part-r-00000"), 3, 3);

    assertNotNull(similarityMatrix);
    assertEquals(3, similarityMatrix.numCols());
    assertEquals(3, similarityMatrix.numRows());

    assertEquals(0.0, similarityMatrix.get(0, 0), EPSILON);
    assertEquals(0.5, similarityMatrix.get(0, 1), EPSILON);
    assertEquals(0.0, similarityMatrix.get(0, 2), EPSILON);
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