org.apache.spark.mllib.linalg.Vector.size()方法的使用及代码示例

x33g5p2x  于2022-02-01 转载在 其他  
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本文整理了Java中org.apache.spark.mllib.linalg.Vector.size()方法的一些代码示例，展示了Vector.size()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.size()方法的具体详情如下：
包路径：org.apache.spark.mllib.linalg.Vector
类名称：Vector
方法名：size

Vector.size介绍

暂无

代码示例

代码示例来源：origin: mahmoudparsian/data-algorithms-book

static Vector average(List<Vector> list) {
  // find sum
  double[] sum = new double[list.get(0).size()];
  for (Vector v : list) {
    for (int i = 0; i < sum.length; i++) {
      sum[i] += v.apply(i);
    }
  }
  // find averages...
  int numOfVectors = list.size();
  for (int i = 0; i < sum.length; i++) {
    sum[i] = sum[i] / numOfVectors;
  }
  return new DenseVector(sum);
}

代码示例来源：origin: mahmoudparsian/data-algorithms-book

static Vector average(Vector vec, Integer numVectors) {
  double[] avg = new double[vec.size()];
  for (int i = 0; i < avg.length; i++) {
    // avg[i] = vec.apply(i) * (1.0 / numVectors);
    avg[i] = vec.apply(i) / ((double) numVectors);
  }
  return new DenseVector(avg);
}

代码示例来源：origin: mahmoudparsian/data-algorithms-book

static double squaredDistance(Vector a, Vector b) {
  double distance = 0.0;
  int size = a.size();
  for (int i = 0; i < size; i++) {
    double diff = a.apply(i) - b.apply(i);
    distance += diff * diff;
  }
  return distance;
}

代码示例来源：origin: mahmoudparsian/data-algorithms-book

static Vector add(Vector a, Vector b) {
  double[] sum = new double[a.size()];
  for (int i = 0; i < sum.length; i++) {
    sum[i] += a.apply(i) + b.apply(i);
  }
  return new DenseVector(sum);
}

代码示例来源：origin: ypriverol/spark-java8

static double squaredDistance(Vector a, Vector b) {
  double distance = 0.0;
  int size = a.size();
  for (int i = 0; i < size; i++) {
    double diff = a.apply(i) - b.apply(i);
    distance += diff * diff;
  }
  return distance;
}

代码示例来源：origin: ypriverol/spark-java8

static Vector average(Vector vec, Integer numVectors) {
  double[] avg = new double[vec.size()];
  for (int i = 0; i < avg.length; i++) {
    // avg[i] = vec.apply(i) * (1.0 / numVectors);
    avg[i] = vec.apply(i) / ((double) numVectors);
  }
  return new DenseVector(avg);
}

代码示例来源：origin: ypriverol/spark-java8

static Vector add(Vector a, Vector b) {
  double[] sum = new double[a.size()];
  for (int i = 0; i < sum.length; i++) {
    sum[i] += a.apply(i) + b.apply(i);
  }
  return new DenseVector(sum);
}

代码示例来源：origin: org.apache.spark/spark-mllib_2.11

@Test
@SuppressWarnings("unchecked")
public void testNormalVectorRDD() {
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = normalJavaVectorRDD(jsc, m, n);
 JavaRDD<Vector> rdd2 = normalJavaVectorRDD(jsc, m, n, p);
 JavaRDD<Vector> rdd3 = normalJavaVectorRDD(jsc, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib_2.10

@Test
@SuppressWarnings("unchecked")
public void testNormalVectorRDD() {
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = normalJavaVectorRDD(jsc, m, n);
 JavaRDD<Vector> rdd2 = normalJavaVectorRDD(jsc, m, n, p);
 JavaRDD<Vector> rdd3 = normalJavaVectorRDD(jsc, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib_2.10

@Test
@SuppressWarnings("unchecked")
public void testPoissonVectorRDD() {
 double mean = 2.0;
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = poissonJavaVectorRDD(jsc, mean, m, n);
 JavaRDD<Vector> rdd2 = poissonJavaVectorRDD(jsc, mean, m, n, p);
 JavaRDD<Vector> rdd3 = poissonJavaVectorRDD(jsc, mean, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib

@Test
@SuppressWarnings("unchecked")
public void testUniformVectorRDD() {
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = uniformJavaVectorRDD(jsc, m, n);
 JavaRDD<Vector> rdd2 = uniformJavaVectorRDD(jsc, m, n, p);
 JavaRDD<Vector> rdd3 = uniformJavaVectorRDD(jsc, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib_2.11

@Test
@SuppressWarnings("unchecked")
public void testUniformVectorRDD() {
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = uniformJavaVectorRDD(jsc, m, n);
 JavaRDD<Vector> rdd2 = uniformJavaVectorRDD(jsc, m, n, p);
 JavaRDD<Vector> rdd3 = uniformJavaVectorRDD(jsc, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib

@Test
@SuppressWarnings("unchecked")
public void testNormalVectorRDD() {
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = normalJavaVectorRDD(jsc, m, n);
 JavaRDD<Vector> rdd2 = normalJavaVectorRDD(jsc, m, n, p);
 JavaRDD<Vector> rdd3 = normalJavaVectorRDD(jsc, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib_2.11

@Test
@SuppressWarnings("unchecked")
public void testPoissonVectorRDD() {
 double mean = 2.0;
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = poissonJavaVectorRDD(jsc, mean, m, n);
 JavaRDD<Vector> rdd2 = poissonJavaVectorRDD(jsc, mean, m, n, p);
 JavaRDD<Vector> rdd3 = poissonJavaVectorRDD(jsc, mean, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib_2.10

@Test
@SuppressWarnings("unchecked")
public void testUniformVectorRDD() {
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = uniformJavaVectorRDD(jsc, m, n);
 JavaRDD<Vector> rdd2 = uniformJavaVectorRDD(jsc, m, n, p);
 JavaRDD<Vector> rdd3 = uniformJavaVectorRDD(jsc, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib_2.11

@Test
@SuppressWarnings("unchecked")
public void testExponentialVectorRDD() {
 double mean = 2.0;
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = exponentialJavaVectorRDD(jsc, mean, m, n);
 JavaRDD<Vector> rdd2 = exponentialJavaVectorRDD(jsc, mean, m, n, p);
 JavaRDD<Vector> rdd3 = exponentialJavaVectorRDD(jsc, mean, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib

@Test
@SuppressWarnings("unchecked")
public void testExponentialVectorRDD() {
 double mean = 2.0;
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = exponentialJavaVectorRDD(jsc, mean, m, n);
 JavaRDD<Vector> rdd2 = exponentialJavaVectorRDD(jsc, mean, m, n, p);
 JavaRDD<Vector> rdd3 = exponentialJavaVectorRDD(jsc, mean, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib_2.10

@Test
@SuppressWarnings("unchecked")
public void testLogNormalVectorRDD() {
 double mean = 4.0;
 double std = 2.0;
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = logNormalJavaVectorRDD(jsc, mean, std, m, n);
 JavaRDD<Vector> rdd2 = logNormalJavaVectorRDD(jsc, mean, std, m, n, p);
 JavaRDD<Vector> rdd3 = logNormalJavaVectorRDD(jsc, mean, std, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib_2.10

@Test
@SuppressWarnings("unchecked")
public void testGammaVectorRDD() {
 double shape = 1.0;
 double jscale = 2.0;
 long m = 100L;
 int n = 10;
 int p = 2;
 long seed = 1L;
 JavaRDD<Vector> rdd1 = gammaJavaVectorRDD(jsc, shape, jscale, m, n);
 JavaRDD<Vector> rdd2 = gammaJavaVectorRDD(jsc, shape, jscale, m, n, p);
 JavaRDD<Vector> rdd3 = gammaJavaVectorRDD(jsc, shape, jscale, m, n, p, seed);
 for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
  Assert.assertEquals(m, rdd.count());
  Assert.assertEquals(n, rdd.first().size());
 }
}

代码示例来源：origin: org.apache.spark/spark-mllib

@Test
 @SuppressWarnings("unchecked")
 public void testRandomVectorRDD() {
  UniformGenerator generator = new UniformGenerator();
  long m = 100L;
  int n = 10;
  int p = 2;
  long seed = 1L;
  JavaRDD<Vector> rdd1 = randomJavaVectorRDD(jsc, generator, m, n);
  JavaRDD<Vector> rdd2 = randomJavaVectorRDD(jsc, generator, m, n, p);
  JavaRDD<Vector> rdd3 = randomJavaVectorRDD(jsc, generator, m, n, p, seed);
  for (JavaRDD<Vector> rdd : Arrays.asList(rdd1, rdd2, rdd3)) {
   Assert.assertEquals(m, rdd.count());
   Assert.assertEquals(n, rdd.first().size());
  }
 }
}

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