Package org.apache.mahout.math.hadoop

Examples of org.apache.mahout.math.hadoop.DistributedRowMatrix.numCols()

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        "--workingDir", workingDir.toString()
    };
    ToolRunner.run(getConfiguration(), new DistributedLanczosSolver().new DistributedLanczosSolverJob(), args);

    Path rawEigenvectors = new Path(output, DistributedLanczosSolver.RAW_EIGENVECTORS);
    Matrix eigenVectors = new DenseMatrix(7, corpus.numCols());
    Configuration conf = getConfiguration();

    int i = 0;
    for (VectorWritable value : new SequenceFileValueIterable<VectorWritable>(rawEigenvectors, conf)) {
      Vector v = value.get();
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        "--cleansvd", "true"
    };
    ToolRunner.run(getConfiguration(), new DistributedLanczosSolver().new DistributedLanczosSolverJob(), args);
 
    Path cleanEigenvectors = new Path(output, EigenVerificationJob.CLEAN_EIGENVECTORS);
    Matrix eigenVectors = new DenseMatrix(6, corpus.numCols());
    Collection<Double> eigenvalues = Lists.newArrayList();

    output = getTestTempDirPath("output2");
    tmp = getTestTempDirPath("tmp2");
    args = new String[] {
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        "--symmetric", "false",
        "--cleansvd", "true"
    };
    ToolRunner.run(getConfiguration(), new DistributedLanczosSolver().new DistributedLanczosSolverJob(), args);
    Path cleanEigenvectors2 = new Path(output, EigenVerificationJob.CLEAN_EIGENVECTORS);
    Matrix eigenVectors2 = new DenseMatrix(7, corpus.numCols());
    Configuration conf = getConfiguration();
    Collection<Double> newEigenValues = Lists.newArrayList();

    int i = 0;
    for (VectorWritable value : new SequenceFileValueIterable<VectorWritable>(cleanEigenvectors, conf)) {
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        "--workingDir", workingDir.toString()
    };
    new DistributedLanczosSolver().new DistributedLanczosSolverJob().run(args);

    Path rawEigenvectors = new Path(output, DistributedLanczosSolver.RAW_EIGENVECTORS);
    Matrix eigenVectors = new DenseMatrix(35, corpus.numCols());
    Configuration conf = new Configuration();

    int i = 0;
    for (VectorWritable value : new SequenceFileValueIterable<VectorWritable>(rawEigenvectors, conf)) {
      Vector v = value.get();
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        "--cleansvd", "true"
    };
    new DistributedLanczosSolver().new DistributedLanczosSolverJob().run(args);
 
    Path cleanEigenvectors = new Path(output, EigenVerificationJob.CLEAN_EIGENVECTORS);
    Matrix eigenVectors = new DenseMatrix(30, corpus.numCols());
    Collection<Double> eigenvalues = new ArrayList<Double>();

    output = getTestTempDirPath("output2");
    tmp = getTestTempDirPath("tmp2");
    args = new String[] {
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        "--symmetric", "false",
        "--cleansvd", "true"
    };
    new DistributedLanczosSolver().new DistributedLanczosSolverJob().run(args);
    Path cleanEigenvectors2 = new Path(output, EigenVerificationJob.CLEAN_EIGENVECTORS);
    Matrix eigenVectors2 = new DenseMatrix(35, corpus.numCols());
    Configuration conf = new Configuration();
    Collection<Double> newEigenValues = new ArrayList<Double>();

    int i = 0;
    for (VectorWritable value : new SequenceFileValueIterable<VectorWritable>(cleanEigenvectors, conf)) {
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    corpus.setConf(conf);
    DistributedLanczosSolver solver = new DistributedLanczosSolver();
    Vector intitialVector = solver.getInitialVector(corpus);
    LanczosState state;
    if(hdfsBackedState) {
      HdfsBackedLanczosState hState = new HdfsBackedLanczosState(corpus, corpus.numCols(),
          desiredRank, intitialVector, new Path(getTestTempDirPath(),
              "lanczosStateDir" + suf(symmetric) + counter));
      hState.setConf(conf);
      state = hState;
    } else {
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          desiredRank, intitialVector, new Path(getTestTempDirPath(),
              "lanczosStateDir" + suf(symmetric) + counter));
      hState.setConf(conf);
      state = hState;
    } else {
      state = new LanczosState(corpus, corpus.numCols(), desiredRank, intitialVector);
    }
    solver.solve(state, desiredRank, symmetric);
    assertOrthonormal(state);
    for(int i = 0; i < desiredRank/2; i++) {
      assertEigen(i, state.getRightSingularVector(i), corpus, 0.1, symmetric);
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    Configuration conf = new Configuration();
    corpus.setConf(conf);
    DistributedLanczosSolver solver = new DistributedLanczosSolver();
    int rank = 10;
    Vector intitialVector = solver.getInitialVector(corpus);
    HdfsBackedLanczosState state = new HdfsBackedLanczosState(corpus, corpus.numCols(), rank,
        intitialVector, new Path(getTestTempDirPath(), "lanczosStateDir" + suf(symmetric) + counter));
    solver.solve(state, rank, symmetric);

    rank *= 2;
    state = new HdfsBackedLanczosState(corpus, corpus.numCols(), rank,
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    HdfsBackedLanczosState state = new HdfsBackedLanczosState(corpus, corpus.numCols(), rank,
        intitialVector, new Path(getTestTempDirPath(), "lanczosStateDir" + suf(symmetric) + counter));
    solver.solve(state, rank, symmetric);

    rank *= 2;
    state = new HdfsBackedLanczosState(corpus, corpus.numCols(), rank,
        intitialVector, new Path(getTestTempDirPath(), "lanczosStateDir" + suf(symmetric) + counter));
    solver = new DistributedLanczosSolver();
    solver.solve(state, rank, symmetric);

    LanczosState allAtOnceState = doTestDistributedLanczosSolver(symmetric, rank, false);
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