org.apache.mahout.math.Vector类的使用及代码示例

x33g5p2x  于2022-02-01 转载在 其他  
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本文整理了Java中org.apache.mahout.math.Vector类的一些代码示例，展示了Vector类的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Vector类的具体详情如下：
包路径：org.apache.mahout.math.Vector
类名称：Vector

Vector介绍

[英]The basic interface including numerous convenience functions

NOTE: All implementing classes must have a constructor that takes an int for cardinality and a no-arg constructor that can be used for marshalling the Writable instance

NOTE: Implementations may choose to reuse the Vector.Element in the Iterable methods
[中]基本界面包括许多方便的功能
注意：所有实现类都必须有一个以int为基数的构造函数和一个可用于封送可写实例的无参数构造函数
注意：实现可能会选择重用向量。Iterable方法中的元素

代码示例

代码示例来源：origin: apache/mahout

@Test
public void testGetDistanceSquared() {
 Vector other = new RandomAccessSparseVector(test.size());
 other.set(1, -2);
 other.set(2, -5);
 other.set(3, -9);
 other.set(4, 1);
 double expected = test.minus(other).getLengthSquared();
 assertTrue("a.getDistanceSquared(b) != a.minus(b).getLengthSquared",
       Math.abs(expected - test.getDistanceSquared(other)) < 10.0E-7);
}

代码示例来源：origin: apache/mahout

Vector hColumn = hessenBerg.viewColumn(m - 1).viewPart(m, high - m + 1);
 double scale = hColumn.norm(1);
  ort.viewPart(m, high - m + 1).assign(hColumn, Functions.plusMult(1 / scale));
  double h = ort.viewPart(m, high - m + 1).getLengthSquared();
  if (ort.getQuick(m) > 0) {
   g = -g;
  h -= ort.getQuick(m) * g;
  ort.setQuick(m, ort.getQuick(m) - g);
  Vector ortPiece = ort.viewPart(m, high - m + 1);
  for (int j = m; j < n; j++) {
   double f = ortPiece.dot(hessenBerg.viewColumn(j).viewPart(m, high - m + 1)) / h;
   hessenBerg.viewColumn(j).viewPart(m, high - m + 1).assign(ortPiece, Functions.plusMult(-f));
   double f = ortPiece.dot(hessenBerg.viewRow(i).viewPart(m, high - m + 1)) / h;
   hessenBerg.viewRow(i).viewPart(m, high - m + 1).assign(ortPiece, Functions.plusMult(-f));
  ort.setQuick(m, scale * ort.getQuick(m));
  hessenBerg.setQuick(m, m - 1, scale * g);
v.viewDiagonal().assign(1);
  ort.viewPart(m + 1, high - m).assign(hessenBerg.viewColumn(m - 1).viewPart(m + 1, high - m));
  for (int j = m; j <= high; j++) {
   double g = ort.viewPart(m, high - m + 1).dot(v.viewColumn(j).viewPart(m, high - m + 1));

代码示例来源：origin: apache/mahout

@Test
public void testPlusDouble() {
 Vector val = test.plus(1);
 assertEquals("size", test.size(), val.size());
 for (int i = 0; i < test.size(); i++) {
  if (i % 2 == 0) {
   assertEquals("get [" + i + ']', 1.0, val.get(i), EPSILON);
  } else {
   assertEquals("get [" + i + ']', values[i/2] + 1.0, val.get(i), EPSILON);
  }
 }
}

代码示例来源：origin: apache/mahout

private Vector localVOrtho(Vector v) {
 for (Vector old : localV) {
  if (old != null) {
   double x = v.dot(old);
   v = v.minus(old.times(x));
  }
 }
 return v;
}

代码示例来源：origin: apache/mahout

@Override
public Vector plus(Vector that) {
 if (size != that.size()) {
  throw new CardinalityException(size, that.size());
 }
 return createOptimizedCopy().assign(that, Functions.PLUS);
}

代码示例来源：origin: apache/mahout

public RandomAccessSparseVector(Vector other) {
 this(other.size(), other.getNumNondefaultElements());
 for (Element e : other.nonZeroes()) {
  values.put(e.index(), e.get());
 }
}

代码示例来源：origin: org.apache.mahout/mahout-mrlegacy

private void initializeM(Vector averageRatings) throws IOException {
 Random random = RandomUtils.getRandom();
 FileSystem fs = FileSystem.get(pathToM(-1).toUri(), getConf());
 SequenceFile.Writer writer = null;
 try {
  writer = new SequenceFile.Writer(fs, getConf(), new Path(pathToM(-1), "part-m-00000"), IntWritable.class,
    VectorWritable.class);
  IntWritable index = new IntWritable();
  VectorWritable featureVector = new VectorWritable();
  for (Vector.Element e : averageRatings.nonZeroes()) {
   Vector row = new DenseVector(numFeatures);
   row.setQuick(0, e.get());
   for (int m = 1; m < numFeatures; m++) {
    row.setQuick(m, random.nextDouble());
   }
   index.set(e.index());
   featureVector.set(row);
   writer.append(index, featureVector);
  }
 } finally {
  Closeables.close(writer, false);
 }
}

代码示例来源：origin: org.apache.mahout/mahout-mrlegacy

@Test
public void toyData() throws Exception {
 TrainNaiveBayesJob trainNaiveBayes = new TrainNaiveBayesJob();
 trainNaiveBayes.setConf(conf);
 trainNaiveBayes.run(new String[] { "--input", inputFile.getAbsolutePath(), "--output", outputDir.getAbsolutePath(),
   "-el", "--tempDir", tempDir.getAbsolutePath() });
 NaiveBayesModel naiveBayesModel = NaiveBayesModel.materialize(new Path(outputDir.getAbsolutePath()), conf);
 AbstractVectorClassifier classifier = new StandardNaiveBayesClassifier(naiveBayesModel);
 assertEquals(2, classifier.numCategories());
 Vector prediction = classifier.classifyFull(trainingInstance(COLOR_RED, TYPE_SUV, ORIGIN_DOMESTIC).get());
 // should be classified as not stolen
 assertTrue(prediction.get(0) < prediction.get(1));
}

代码示例来源：origin: org.apache.mahout/mahout-core

public static NaiveBayesModel materialize(Path output, Configuration conf) throws IOException {
 FileSystem fs = output.getFileSystem(conf);
 Vector weightsPerLabel = null;
 Vector perLabelThetaNormalizer = null;
 Vector weightsPerFeature = null;
 Matrix weightsPerLabelAndFeature;
 float alphaI;
 FSDataInputStream in = fs.open(new Path(output, "naiveBayesModel.bin"));
 try {
  alphaI = in.readFloat();
  weightsPerFeature = VectorWritable.readVector(in);
  weightsPerLabel = new DenseVector(VectorWritable.readVector(in));
  perLabelThetaNormalizer = new DenseVector(VectorWritable.readVector(in));
  weightsPerLabelAndFeature = new SparseRowMatrix(weightsPerLabel.size(), weightsPerFeature.size());
  for (int label = 0; label < weightsPerLabelAndFeature.numRows(); label++) {
   weightsPerLabelAndFeature.assignRow(label, VectorWritable.readVector(in));
  }
 } finally {
  Closeables.close(in, true);
 }
 NaiveBayesModel model = new NaiveBayesModel(weightsPerLabelAndFeature, weightsPerFeature, weightsPerLabel,
   perLabelThetaNormalizer, alphaI);
 model.validate();
 return model;
}

代码示例来源：origin: intel-hadoop/HiBench

SequenceFile.Writer out;
int fileNo = 0;
out = createNewFile(new Path(samplePath, "file" + (fileNo++)));
double[] vec = new double[this.dimension];
while ((s = in.readLine()) != null) {
  Vector p = new RandomAccessSparseVector(dimension);
  p.assign(vec);
  if (samplesInCurrFile >= SAMPLES_PER_FILE) {
    out.close();
    out = createNewFile(new Path(samplePath, "file" + (fileNo++)));
    samplesInCurrFile = 0;
  out.append(new LongWritable(samplesInCurrFile++), new VectorWritable(p));
  sampleNum++;

代码示例来源：origin: org.apache.mahout/mahout-core

@Override
 protected void map(IntWritable r, VectorWritable v, Context ctx) throws IOException, InterruptedException {
  int row = r.get();
  for (Vector.Element e : v.get().nonZeroes()) {
   RandomAccessSparseVector tmp = new RandomAccessSparseVector(Integer.MAX_VALUE, 1);
   tmp.setQuick(row, e.get());
   r.set(e.index());
   ctx.write(r, new VectorWritable(tmp));
  }
 }
}

代码示例来源：origin: org.apache.mahout/mahout-mr

@Override
protected void map(IntWritable index, VectorWritable value, Context ctx) throws IOException, InterruptedException {
 Vector instance = value.get();
 if (weightsPerFeature == null) {
  weightsPerFeature = new RandomAccessSparseVector(instance.size(), instance.getNumNondefaultElements());
 }
 int label = index.get();
 weightsPerFeature.assign(instance, Functions.PLUS);
 weightsPerLabel.set(label, weightsPerLabel.get(label) + instance.zSum());
}

代码示例来源：origin: org.apache.mahout/mahout-mrlegacy

private void validateVectors(Path vectorPath, int[] highDFWordsDictionaryIndices, boolean prune) throws Exception {
  assertTrue("Path does not exist", vectorPath.getFileSystem(conf).exists(vectorPath));
  for (VectorWritable value : new SequenceFileDirValueIterable<VectorWritable>(vectorPath, PathType.LIST, PathFilters
      .partFilter(), null, true, conf)) {
   Vector v = ((NamedVector) value.get()).getDelegate();
   for (int i = 0; i < highDFWordsDictionaryIndices.length; i++) {
    if (prune) {
     assertEquals("Found vector for which word '" + HIGH_DF_WORDS[i] + "' is not pruned", 0.0, v
       .get(highDFWordsDictionaryIndices[i]), 0.0);
    } else {
     assertTrue("Found vector for which word '" + HIGH_DF_WORDS[i] + "' is pruned, and shouldn't have been", v
         .get(highDFWordsDictionaryIndices[i]) != 0.0);
    }
   }
  }
 }
}

代码示例来源：origin: org.apache.mahout/mahout-mrlegacy

@Override
protected void map(IntWritable key,
          VectorWritable value,
          Context context) throws IOException, InterruptedException {
 Vector similarityMatrixRow = value.get();
 /* remove self similarity */
 similarityMatrixRow.set(key.get(), Double.NaN);
 index.set(key.get());
 vectorOrPref.set(similarityMatrixRow);
 context.write(index, vectorOrPref);
}

代码示例来源：origin: apache/mahout

Vector v1 = v0.assign(new Normal(0, 1, gen));
assertEquals(v0.get(12), v1.get(12), 0);
v0.set(12, gen.nextDouble());
assertEquals(v0.get(12), v1.get(12), 0);
assertSame(v0, v1);
Vector v2 = vectorToTest(20).assign(new Normal(0, 1, gen));
Vector dv1 = new DenseVector(v1);
Vector dv2 = new DenseVector(v2);
Vector sv1 = new RandomAccessSparseVector(v1);
Vector sv2 = new RandomAccessSparseVector(v2);
assertEquals(0, dv1.plus(dv2).getDistanceSquared(v1.plus(v2)), FUZZ);
assertEquals(0, dv1.plus(dv2).getDistanceSquared(v1.plus(dv2)), FUZZ);
assertEquals(0, dv1.plus(dv2).getDistanceSquared(v1.plus(sv2)), FUZZ);
assertEquals(0, dv1.plus(dv2).getDistanceSquared(sv1.plus(v2)), FUZZ);
assertEquals(0, dv1.times(dv2).getDistanceSquared(v1.times(v2)), FUZZ);
assertEquals(0, dv1.times(dv2).getDistanceSquared(v1.times(dv2)), FUZZ);
assertEquals(0, dv1.times(dv2).getDistanceSquared(v1.times(sv2)), FUZZ);
assertEquals(0, dv1.times(dv2).getDistanceSquared(sv1.times(v2)), FUZZ);
assertEquals(0, dv1.minus(dv2).getDistanceSquared(v1.minus(v2)), FUZZ);
assertEquals(0, dv1.minus(dv2).getDistanceSquared(v1.minus(dv2)), FUZZ);
assertEquals(0, dv1.minus(dv2).getDistanceSquared(v1.minus(sv2)), FUZZ);
assertEquals(0, dv1.minus(dv2).getDistanceSquared(sv1.minus(v2)), FUZZ);
assertEquals(0, dv1.divide(z).getDistanceSquared(v1.divide(z)), 1.0e-12);

代码示例来源：origin: tdunning/MiA

public void reduce(IntWritable itemIndex1,
      Iterable<IntWritable> itemIndex2s, Context context)
      throws IOException, InterruptedException {
    Vector cooccurrenceRow = new RandomAccessSparseVector(
        Integer.MAX_VALUE, 100);
    for (IntWritable intWritable : itemIndex2s) {
      int itemIndex2 = intWritable.get();
      cooccurrenceRow.set(itemIndex2,
          cooccurrenceRow.get(itemIndex2) + 1.0);
    }
    context.write(itemIndex1, new VectorWritable(cooccurrenceRow));
  }
}

代码示例来源：origin: org.apache.mahout/mahout-mrlegacy

@Override
 protected void map(IntWritable r, VectorWritable v, Context ctx) throws IOException, InterruptedException {
  RunningAverage avg = new FullRunningAverage();
  for (Vector.Element e : v.get().nonZeroes()) {
   avg.addDatum(e.get());
  }
  featureVector.setQuick(r.get(), avg.getAverage());
  featureVectorWritable.set(featureVector);
  ctx.write(firstIndex, featureVectorWritable);
  // prepare instance for reuse
  featureVector.setQuick(r.get(), 0.0d);
 }
}

代码示例来源：origin: org.apache.mahout/mahout-mrlegacy

@Override
public Vector classify(Vector data, ClusterClassifier prior) {
 List<Cluster> models = prior.getModels();
 int i = 0;
 Vector pdfs = new DenseVector(models.size());
 for (Cluster model : models) {
  pdfs.set(i++, model.pdf(new VectorWritable(data)));
 }
 return pdfs.assign(new TimesFunction(), 1.0 / pdfs.zSum());
}

代码示例来源：origin: apache/mahout

vec1.setQuick(0, -1);
vec1.setQuick(1, -3);
vec1.setQuick(2, -2);
double max = vec1.maxValue();
assertEquals(-1.0, max, 0.0);
int idx = vec1.maxValueIndex();
assertEquals(0, idx);
vec1.setQuick(0, -1);
vec1.setQuick(2, -2);
max = vec1.maxValue();
assertEquals(0.0, max, 0.0);
idx = vec1.maxValueIndex();
assertEquals(1, idx);
vec1.setQuick(0, -1);
vec1.setQuick(2, -2);
max = vec1.maxValue();
assertEquals(0.0, max, 0.0);
idx = vec1.maxValueIndex();
assertEquals(1, idx);
vec1.setQuick(0, -1);

代码示例来源：origin: apache/mahout

@Test
public void testProjection() {
 Vector v1 = new DenseVector(10).assign(Functions.random());
 WeightedVector v2 = new WeightedVector(v1, v1, 31);
 assertEquals(v1.dot(v1), v2.getWeight(), 1.0e-13);
 assertEquals(31, v2.getIndex());
 Matrix y = new DenseMatrix(10, 4).assign(Functions.random());
 Matrix q = new QRDecomposition(y.viewPart(0, 10, 0, 3)).getQ();
 Vector nullSpace = y.viewColumn(3).minus(q.times(q.transpose().times(y.viewColumn(3))));
 WeightedVector v3 = new WeightedVector(q.viewColumn(0).plus(q.viewColumn(1)), nullSpace, 1);
 assertEquals(0, v3.getWeight(), 1.0e-13);
 Vector qx = q.viewColumn(0).plus(q.viewColumn(1)).normalize();
 WeightedVector v4 = new WeightedVector(qx, q.viewColumn(0), 2);
 assertEquals(Math.sqrt(0.5), v4.getWeight(), 1.0e-13);
 WeightedVector v5 = WeightedVector.project(q.viewColumn(0), qx);
 assertEquals(Math.sqrt(0.5), v5.getWeight(), 1.0e-13);
}

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