From b1b7dab57dbc10e7a661cd6f670d7470f6c63cd0 Mon Sep 17 00:00:00 2001
From: Xiangrui Meng <meng@databricks.com>
Date: Tue, 8 Apr 2014 20:11:47 -0700
Subject: [PATCH] fix code styles

---
 .../BinaryClassificationEvaluator.scala       | 34 ++++++++++---------
 1 file changed, 18 insertions(+), 16 deletions(-)

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/evaluation/binary/BinaryClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/mllib/evaluation/binary/BinaryClassificationEvaluator.scala
index 290d8fe127ec7..56a14c6e42adb 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/evaluation/binary/BinaryClassificationEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/evaluation/binary/BinaryClassificationEvaluator.scala
@@ -56,7 +56,8 @@ private case class BinaryConfusionMatrixImpl(
  *
  * @param scoreAndLabels an RDD of (score, label) pairs.
  */
-class BinaryClassificationEvaluator(scoreAndLabels: RDD[(Double, Double)]) extends Serializable with Logging {
+class BinaryClassificationEvaluator(scoreAndLabels: RDD[(Double, Double)])
+    extends Serializable with Logging {
 
   private lazy val (
       cumCounts: RDD[(Double, LabelCounter)],
@@ -73,16 +74,18 @@ class BinaryClassificationEvaluator(scoreAndLabels: RDD[(Double, Double)]) exten
       iter.foreach(agg += _)
       Iterator(agg)
     }, preservesPartitioning = true).collect()
-    val partitionwiseCumCounts = agg.scanLeft(new LabelCounter())((agg: LabelCounter, c: LabelCounter) => agg + c)
+    val partitionwiseCumCounts =
+      agg.scanLeft(new LabelCounter())((agg: LabelCounter, c: LabelCounter) => agg.clone() += c)
     val totalCount = partitionwiseCumCounts.last
     logInfo(s"Total counts: $totalCount")
-    val cumCounts = counts.mapPartitionsWithIndex((index: Int, iter: Iterator[(Double, LabelCounter)]) => {
-      val cumCount = partitionwiseCumCounts(index)
-      iter.map { case (score, c) =>
-        cumCount += c
-        (score, cumCount.clone())
-      }
-    }, preservesPartitioning = true)
+    val cumCounts = counts.mapPartitionsWithIndex(
+      (index: Int, iter: Iterator[(Double, LabelCounter)]) => {
+        val cumCount = partitionwiseCumCounts(index)
+        iter.map { case (score, c) =>
+          cumCount += c
+          (score, cumCount.clone())
+        }
+      }, preservesPartitioning = true)
     cumCounts.persist()
     val confusions = cumCounts.map { case (score, cumCount) =>
       (score, BinaryConfusionMatrixImpl(cumCount, totalCount).asInstanceOf[BinaryConfusionMatrix])
@@ -136,7 +139,9 @@ class BinaryClassificationEvaluator(scoreAndLabels: RDD[(Double, Double)]) exten
   }
 
   /** Creates a curve of (metricX, metricY). */
-  private def createCurve(x: BinaryClassificationMetric, y: BinaryClassificationMetric): RDD[(Double, Double)] = {
+  private def createCurve(
+      x: BinaryClassificationMetric,
+      y: BinaryClassificationMetric): RDD[(Double, Double)] = {
     confusions.map { case (_, c) =>
       (x(c), y(c))
     }
@@ -149,7 +154,9 @@ class BinaryClassificationEvaluator(scoreAndLabels: RDD[(Double, Double)]) exten
  * @param numPositives number of positive labels
  * @param numNegatives number of negative labels
  */
-private class LabelCounter(var numPositives: Long = 0L, var numNegatives: Long = 0L) extends Serializable {
+private class LabelCounter(
+    var numPositives: Long = 0L,
+    var numNegatives: Long = 0L) extends Serializable {
 
   /** Processes a label. */
   def +=(label: Double): LabelCounter = {
@@ -166,11 +173,6 @@ private class LabelCounter(var numPositives: Long = 0L, var numNegatives: Long =
     this
   }
 
-  /** Sums this counter and another counter and returns the result in a new counter. */
-  def +(other: LabelCounter): LabelCounter = {
-    this.clone() += other
-  }
-
   override def clone: LabelCounter = {
     new LabelCounter(numPositives, numNegatives)
   }