remove ;this from setters

apache · Nov 11, 2014 · 0435076 · 0435076
1 parent fa21d9b
commit 0435076
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Showing 6 changed files with 25 additions and 28 deletions.
diff --git a/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala b/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala
@@ -86,8 +86,8 @@ abstract class Transformer extends PipelineStage with Params {
 abstract class UnaryTransformer[IN, OUT: TypeTag, T <: UnaryTransformer[IN, OUT, T]]
   extends Transformer with HasInputCol with HasOutputCol with Logging {
 
-  def setInputCol(value: String): T = { set(inputCol, value); this.asInstanceOf[T] }
-  def setOutputCol(value: String): T = { set(outputCol, value); this.asInstanceOf[T] }
+  def setInputCol(value: String): T = set(inputCol, value).asInstanceOf[T]
+  def setOutputCol(value: String): T = set(outputCol, value).asInstanceOf[T]
 
   /**
    * Creates the transform function using the given param map. The input param map already takes

diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
@@ -75,13 +75,13 @@ class LogisticRegression extends Estimator[LogisticRegressionModel] with Logisti
   setMaxIter(100)
   setThreshold(0.5)
 
-  def setRegParam(value: Double): this.type = { set(regParam, value); this }
-  def setMaxIter(value: Int): this.type = { set(maxIter, value); this }
-  def setLabelCol(value: String): this.type = { set(labelCol, value); this }
-  def setThreshold(value: Double): this.type = { set(threshold, value); this }
-  def setFeaturesCol(value: String): this.type = { set(featuresCol, value); this }
-  def setScoreCol(value: String): this.type = { set(scoreCol, value); this }
-  def setPredictionCol(value: String): this.type = { set(predictionCol, value); this }
+  def setRegParam(value: Double): this.type = set(regParam, value)
+  def setMaxIter(value: Int): this.type = set(maxIter, value)
+  def setLabelCol(value: String): this.type = set(labelCol, value)
+  def setThreshold(value: Double): this.type = set(threshold, value)
+  def setFeaturesCol(value: String): this.type = set(featuresCol, value)
+  def setScoreCol(value: String): this.type = set(scoreCol, value)
+  def setPredictionCol(value: String): this.type = set(predictionCol, value)
 
   override def fit(dataset: SchemaRDD, paramMap: ParamMap): LogisticRegressionModel = {
     transform(dataset.schema, paramMap, logging = true)
@@ -116,10 +116,10 @@ class LogisticRegressionModel private[ml] (
     val weights: Vector)
   extends Model[LogisticRegressionModel] with LogisticRegressionParams {
 
-  def setThreshold(value: Double): this.type = { set(threshold, value); this }
-  def setFeaturesCol(value: String): this.type = { set(featuresCol, value); this }
-  def setScoreCol(value: String): this.type = { set(scoreCol, value); this }
-  def setPredictionCol(value: String): this.type = { set(predictionCol, value); this }
+  def setThreshold(value: Double): this.type = set(threshold, value)
+  def setFeaturesCol(value: String): this.type = set(featuresCol, value)
+  def setScoreCol(value: String): this.type = set(scoreCol, value)
+  def setPredictionCol(value: String): this.type = set(predictionCol, value)
 
   override def transform(schema: StructType, paramMap: ParamMap): StructType = {
     transformSchema(schema, paramMap, fitting = false)

diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
@@ -32,10 +32,10 @@ class BinaryClassificationEvaluator extends Evaluator with Params
   val metricName: Param[String] = new Param(this, "metricName",
     "metric name in evaluation (areaUnderROC|areaUnderPR)", Some("areaUnderROC"))
   def getMetricName: String = get(metricName)
-  def setMetricName(value: String): this.type = { set(metricName, value); this }
+  def setMetricName(value: String): this.type = set(metricName, value)
 
-  def setScoreCol(value: String): this.type = { set(scoreCol, value); this }
-  def setLabelCol(value: String): this.type = { set(labelCol, value); this }
+  def setScoreCol(value: String): this.type = set(scoreCol, value)
+  def setLabelCol(value: String): this.type = set(labelCol, value)
 
   override def evaluate(dataset: SchemaRDD, paramMap: ParamMap): Double = {
     val map = this.paramMap ++ paramMap

diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala
@@ -29,7 +29,7 @@ class HashingTF extends UnaryTransformer[Iterable[_], Vector, HashingTF] {
 
   /** number of features */
   val numFeatures = new IntParam(this, "numFeatures", "number of features", Some(1 << 18))
-  def setNumFeatures(value: Int) = { set(numFeatures, value); this }
+  def setNumFeatures(value: Int) = set(numFeatures, value)
   def getNumFeatures: Int = get(numFeatures)
 
   override protected def createTransformFunc(paramMap: ParamMap): Iterable[_] => Vector = {

diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala
@@ -36,8 +36,8 @@ private[feature] trait StandardScalerParams extends Params with HasInputCol with
  */
 class StandardScaler extends Estimator[StandardScalerModel] with StandardScalerParams {
 
-  def setInputCol(value: String): this.type = { set(inputCol, value); this }
-  def setOutputCol(value: String): this.type = { set(outputCol, value); this }
+  def setInputCol(value: String): this.type = set(inputCol, value)
+  def setOutputCol(value: String): this.type = set(outputCol, value)
 
   override def fit(dataset: SchemaRDD, paramMap: ParamMap): StandardScalerModel = {
     transform(dataset.schema, paramMap, logging = true)
@@ -74,8 +74,8 @@ class StandardScalerModel private[ml] (
     scaler: feature.StandardScalerModel)
   extends Model[StandardScalerModel] with StandardScalerParams {
 
-  def setInputCol(value: String): this.type = { set(inputCol, value); this }
-  def setOutputCol(value: String): this.type = { set(outputCol, value); this }
+  def setInputCol(value: String): this.type = set(inputCol, value)
+  def setOutputCol(value: String): this.type = set(outputCol, value)
 
   override def transform(dataset: SchemaRDD, paramMap: ParamMap): SchemaRDD = {
     transform(dataset.schema, paramMap, logging = true)

diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
@@ -55,13 +55,10 @@ class CrossValidator extends Estimator[CrossValidatorModel] with CrossValidatorP
 
   private val f2jBLAS = new F2jBLAS
 
-  def setEstimator(value: Estimator[_]): this.type = { set(estimator, value); this }
-  def setEstimatorParamMaps(value: Array[ParamMap]): this.type = {
-    set(estimatorParamMaps, value)
-    this
-  }
-  def setEvaluator(value: Evaluator): this.type = { set(evaluator, value); this }
-  def setNumFolds(value: Int): this.type = { set(numFolds, value); this }
+  def setEstimator(value: Estimator[_]): this.type = set(estimator, value)
+  def setEstimatorParamMaps(value: Array[ParamMap]): this.type = set(estimatorParamMaps, value)
+  def setEvaluator(value: Evaluator): this.type = set(evaluator, value)
+  def setNumFolds(value: Int): this.type = set(numFolds, value)
 
   override def fit(dataset: SchemaRDD, paramMap: ParamMap): CrossValidatorModel = {
     val map = this.paramMap ++ paramMap