Package org.apache.mahout.math

Examples of org.apache.mahout.math.RandomAccessSparseVector

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    assertEquals(0.0, expected.getDistanceSquared(actual), EPSILON);
  }

  @Test
  public void testMatrixTimesSquaredVector() throws Exception {
    Vector v = new RandomAccessSparseVector(50);
    v.assign(1.0);
    Matrix m = SolverTest.randomSequentialAccessSparseMatrix(100, 90, 50, 20, 1.0);
    DistributedRowMatrix dm = randomDistributedMatrix(100, 90, 50, 20, 1.0, false);

    Vector expected = m.timesSquared(v);
    Vector actual = dm.timesSquared(v);
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    Path baseTmpDirPath = getTestTempDirPath("testpaths");   
    Path inputPath = new Path(baseTmpDirPath, "input");
    Path outputPath = new Path(baseTmpDirPath, "output");

    Vector v = new RandomAccessSparseVector(50);
    v.assign(1.0);

    Configuration timesSquaredJobConf1 = TimesSquaredJob.createTimesSquaredJobConf(v, inputPath, outputPath);
    Configuration customTimesSquaredJobConf1 = TimesSquaredJob.createTimesSquaredJobConf(initialConf, v, inputPath, outputPath);

    assertNull(timesSquaredJobConf1.get(TEST_PROPERTY_KEY));
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  }
 
  private static List<VectorWritable> getPointsWritable(double[][] raw) {
    List<VectorWritable> points = Lists.newArrayList();
    for (double[] fr : raw) {
      Vector vec = new RandomAccessSparseVector(fr.length);
      vec.assign(fr);
      points.add(new VectorWritable(vec));
    }
    return points;
  }
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  }
 
  @Test
  public void testTimesVectorTempDirDeletion() throws Exception {
    Configuration conf = new Configuration();
    Vector v = new RandomAccessSparseVector(50);
    v.assign(1.0);
    DistributedRowMatrix dm = randomDistributedMatrix(100, 90, 50, 20, 1.0, false);

    Path outputPath = dm.getOutputTempPath();
    FileSystem fs = outputPath.getFileSystem(conf);
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  }

  @Test
  public void testTimesSquaredVectorTempDirDeletion() throws Exception {
    Configuration conf = new Configuration();
    Vector v = new RandomAccessSparseVector(50);
    v.assign(1.0);
    DistributedRowMatrix dm = randomDistributedMatrix(100, 90, 50, 20, 1.0, false);

    Path outputPath = dm.getOutputTempPath();
    FileSystem fs = outputPath.getFileSystem(conf);
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  }
 
  public static List<VectorWritable> getPointsWritable(double[][] raw) {
    List<VectorWritable> points = Lists.newArrayList();
    for (double[] fr : raw) {
      Vector vec = new RandomAccessSparseVector(fr.length);
      vec.assign(fr);
      points.add(new VectorWritable(vec));
    }
    return points;
  }
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   * Generate random document vector
   * @param numWords int number of words in the vocabulary
   * @param numWords E[count] for each word
   */
  private RandomAccessSparseVector generateRandomDoc(int numWords, double sparsity) throws MathException {
    RandomAccessSparseVector v = new RandomAccessSparseVector(numWords,(int)(numWords * sparsity));
    IntegerDistribution dist = new PoissonDistributionImpl(sparsity);
    for (int i = 0; i < numWords; i++) {
      // random integer
      v.set(i,dist.inverseCumulativeProbability(random.nextDouble()) + 1);
    }
    return v;
  }
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  public void testMapper() throws Exception {
    LDAState state = generateRandomState(100,NUM_TOPICS);
    LDAWordTopicMapper mapper = new LDAWordTopicMapper();
    mapper.configure(state);
    for(int i = 0; i < NUM_TESTS; ++i) {
      RandomAccessSparseVector v = generateRandomDoc(100,0.3);
      int myNumWords = numNonZero(v);
      LDAWordTopicMapper.Context mock = EasyMock.createMock(LDAWordTopicMapper.Context.class);

      mock.write(EasyMock.isA(IntPairWritable.class), EasyMock.isA(DoubleWritable.class));
      EasyMock.expectLastCall().times(myNumWords * NUM_TOPICS + NUM_TOPICS + 1);
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  }

  public static List<VectorWritable> getPointsWritable(double[][] raw) {
    List<VectorWritable> points = Lists.newArrayList();
    for (double[] fr : raw) {
      Vector vec = new RandomAccessSparseVector(fr.length);
      vec.assign(fr);
      points.add(new VectorWritable(vec));
    }
    return points;
  }
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  @Override
  protected void setup(Context ctx) throws IOException, InterruptedException {
    int numLabels = Integer.parseInt(ctx.getConfiguration().get(NUM_LABELS));
    Preconditions.checkArgument(numLabels > 0);
    weightsPerLabel = new RandomAccessSparseVector(numLabels);
  }
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