Package org.apache.mahout.math

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

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    Matrix lastWeightMatrix = this.weightMatrixList.get(this.weightMatrixList.size() - 1);

    for (int i = 0; i < deltaVec.size(); ++i) {
      double costFuncDerivative = costFunction.apply(labels.get(i), output.get(i + 1));
      // add regularization
      costFuncDerivative += this.regularizationWeight * lastWeightMatrix.viewRow(i).zSum();
      deltaVec.set(i, costFuncDerivative);
      deltaVec.set(i, deltaVec.get(i) * derivativeSquashingFunction.apply(output.get(i + 1)));
    }

    // start from previous layer of output layer
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    Matrix topicTermCounts = new DenseMatrix(numTopics, numTerms);
    Vector topicSums = new DenseVector(numTopics);
    if (random != null) {
      for (int x = 0; x < numTopics; x++) {
        for (int term = 0; term < numTerms; term++) {
          topicTermCounts.viewRow(x).set(term, random.nextDouble());
        }
      }
    }
    for (int x = 0; x < numTopics; x++) {
      topicSums.set(x, random == null ? 1.0 : topicTermCounts.viewRow(x).norm(1));
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          topicTermCounts.viewRow(x).set(term, random.nextDouble());
        }
      }
    }
    for (int x = 0; x < numTopics; x++) {
      topicSums.set(x, random == null ? 1.0 : topicTermCounts.viewRow(x).norm(1));
    }
    return Pair.of(topicTermCounts, topicSums);
  }

  public static Pair<Matrix, Vector> loadModel(Configuration conf, Path... modelPaths)
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    }
    numTopics++;
    Matrix model = new DenseMatrix(numTopics, numTerms);
    Vector topicSums = new DenseVector(numTopics);
    for (Pair<Integer, Vector> pair : rows) {
      model.viewRow(pair.getFirst()).assign(pair.getSecond());
      topicSums.set(pair.getFirst(), pair.getSecond().norm(1));
    }
    return Pair.of(model, topicSums);
  }
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    // Put the centroids into a matrix.
    Matrix x = new DenseMatrix(6, 5);
    int row = 0;
    for (Centroid c : r) {
      x.viewRow(row).assign(c.viewPart(0, 5));
      row++;
    }

    // Verify that each column looks right. Should contain zeros except for a single 6.
    final Vector columnNorms = x.aggregateColumns(new VectorFunction() {
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        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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        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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      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 {
      Closeables.closeQuietly(writer);
    }
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    Matrix topicTermCounts = new DenseMatrix(numTopics, numTerms);
    Vector topicSums = new DenseVector(numTopics);
    if (random != null) {
      for (int x = 0; x < numTopics; x++) {
        for (int term = 0; term < numTerms; term++) {
          topicTermCounts.viewRow(x).set(term, random.nextDouble());
        }
      }
    }
    for (int x = 0; x < numTopics; x++) {
      topicSums.set(x, random == null ? 1.0 : topicTermCounts.viewRow(x).norm(1));
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          topicTermCounts.viewRow(x).set(term, random.nextDouble());
        }
      }
    }
    for (int x = 0; x < numTopics; x++) {
      topicSums.set(x, random == null ? 1.0 : topicTermCounts.viewRow(x).norm(1));
    }
    return Pair.of(topicTermCounts, topicSums);
  }

  public static Pair<Matrix, Vector> loadModel(Configuration conf, Path... modelPaths)
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