Rewrite scala stream demos

demo-scala/src/UnweightedStream.scala

@@ -1,25 +1,44 @@
 import java.util.Random
 
+import SamplingIterator._
 import gr.james.sampling.{RandomSampling, WatermanSampling}
 
 import scala.collection.JavaConverters._
 
 /**
-  * Unweighted random sampling using functional constructs.
+  * Extension of the [[Iterator]] with the <code>sample</code> method.
+  *
+  * @param it the source iterator
+  * @tparam T the element type
   */
-object UnweightedStream extends App {
-  val sample = (0 until 20)
-    .foldLeft(construct[Int](5, new Random()))(foldOperation)
-    .sample().asScala.toList
-
-  def construct[T](sample: Int, random: Random): RandomSampling[T] =
-    new WatermanSampling[T](sample, random)
-
-  def foldOperation[T] =
+class SamplingIterator[T](val it: Iterator[T]) {
+  private val foldOperation =
     (rs: RandomSampling[T], i: T) => {
       rs.feed(i)
       rs
     }
 
+  /**
+    * Samples this iterator using the provided algorithm.
+    *
+    * @param rs the sampling algorithm
+    * @return a [[List]] containing the sampled elements
+    */
+  def sample(rs: RandomSampling[T]): List[T] = it.foldLeft(rs)(foldOperation).sample().asScala.toList
+}
+
+/**
+  * The [[SamplingIterator]] companion object with the <code>iteratorToSamplingIterator</code> implicit conversion.
+  */
+object SamplingIterator {
+  implicit def iteratorToSamplingIterator[T](s: Iterator[T]): SamplingIterator[T] =
+    new SamplingIterator(s)
+}
+
+/**
+  * Unweighted random sampling using functional constructs.
+  */
+object UnweightedStream extends App {
+  val sample = (0 until 20).iterator.sample(new WatermanSampling[Int](5, new Random()))
   println(sample)
 }

demo-scala/src/WeightedStream.scala

@@ -1,33 +1,52 @@
 import java.util.Random
 
+import WeightedSamplingIterator._
 import gr.james.sampling.{ChaoSampling, WeightedRandomSampling}
 
 import scala.collection.JavaConverters._
 
+/**
+  * Extension of the [[Iterator]] with the <code>sample</code> method.
+  *
+  * @param it the source iterator
+  * @tparam T the element type
+  */
+class WeightedSamplingIterator[T](val it: Iterator[(T, Double)]) {
+  private val foldOperation =
+    (rs: WeightedRandomSampling[T], i: (T, Double)) => {
+      rs.feed(i._1, i._2)
+      rs
+    }
+
+  /**
+    * Samples this iterator using the provided algorithm.
+    *
+    * @param wrs the sampling algorithm
+    * @return a [[List]] containing the sampled elements
+    */
+  def sample(wrs: WeightedRandomSampling[T]): List[T] = it.foldLeft(wrs)(foldOperation).sample().asScala.toList
+}
+
+/**
+  * The [[WeightedSamplingIterator]] companion object with the <code>iteratorToWeightedSamplingIterator</code> implicit
+  * conversion.
+  */
+object WeightedSamplingIterator {
+  implicit def iteratorToWeightedSamplingIterator[T](s: Iterator[(T, Double)]): WeightedSamplingIterator[T] =
+    new WeightedSamplingIterator(s)
+}
+
 /**
   * Weighted random sampling using functional constructs.
   */
 object WeightedStream extends App {
-  val map = Map(
+  val sample = Map(
     "collection" -> 1.0,
     "algorithms" -> 2.0,
     "java" -> 2.0,
     "random" -> 3.0,
     "sampling" -> 4.0,
     "reservoir" -> 5.0
-  )
-  val sample = map
-    .foldLeft(construct[String](2, new Random()))(foldOperation)
-    .sample().asScala.toList
-
-  def construct[T](sample: Int, random: Random): WeightedRandomSampling[T] =
-    new ChaoSampling[T](sample, random)
-
-  def foldOperation[T] =
-    (wrs: WeightedRandomSampling[T], i: (T, Double)) => {
-      wrs.feed(i._1, i._2)
-      wrs
-    }
-
+  ).iterator.sample(new ChaoSampling[String](2, new Random))
   println(sample)
 }