Router: ignore line breaks for blocks

repos/PredictionIO/core/src/main/scala/io/prediction/controller/Engine.scala

@@ -335,9 +335,8 @@ class Engine[TD, EI, PD, Q, P, A](
 
     val algorithms = algoParamsList.map {
       case (algoName, algoParams) => {
-        try {
-          Doer(algorithmClassMap(algoName), algoParams)
-        } catch {
+        try { Doer(algorithmClassMap(algoName), algoParams) }
+        catch {
           case e: NoSuchElementException => {
             if (algoName == "") {
               logger.error(
@@ -647,16 +646,12 @@ object Engine {
     logger.info(s"Preparator: $preparator")
     logger.info(s"AlgorithmList: $algorithmList")
 
-    if (params.skipSanityCheck) {
-      logger.info("Data sanity check is off.")
-    } else {
-      logger.info("Data sanity check is on.")
-    }
+    if (params.skipSanityCheck) { logger.info("Data sanity check is off.") }
+    else { logger.info("Data sanity check is on.") }
 
     val td =
-      try {
-        dataSource.readTrainingBase(sc)
-      } catch {
+      try { dataSource.readTrainingBase(sc) }
+      catch {
         case e: StorageClientException =>
           logger.error(
             s"Error occured reading from data source. (Reason: " +
@@ -783,15 +778,11 @@ object Engine {
       .mapValues { _.zipWithUniqueId().map(_.swap) }
 
     val preparedMap: Map[EX, PD] = evalTrainMap.mapValues { td =>
-      {
-        preparator.prepareBase(sc, td)
-      }
+      { preparator.prepareBase(sc, td) }
     }
 
     val algoModelsMap: Map[EX, Map[AX, Any]] = preparedMap.mapValues { pd =>
-      {
-        algoMap.mapValues(_.trainBase(sc, pd))
-      }
+      { algoMap.mapValues(_.trainBase(sc, pd)) }
     }
 
     val suppQAsMap: Map[EX, RDD[(QX, (Q, A))]] = evalQAsMap.mapValues { qas =>
@@ -813,9 +804,7 @@ object Engine {
                 val rawPredicts: RDD[(QX, P)] =
                   algo.batchPredictBase(sc, model, qs)
                 val predicts: RDD[(QX, (AX, P))] = rawPredicts.map {
-                  case (qx, p) => {
-                    (qx, (ax, p))
-                  }
+                  case (qx, p) => { (qx, (ax, p)) }
                 }
                 predicts
               }
@@ -856,9 +845,7 @@ object Engine {
       }
 
     (0 until evalCount).map { ex =>
-      {
-        (evalInfoMap(ex), servingQPAMap(ex))
-      }
+      { (evalInfoMap(ex), servingQPAMap(ex)) }
     }.toSeq
   }
 }

repos/PredictionIO/core/src/main/scala/io/prediction/controller/FastEvalEngine.scala

@@ -266,9 +266,7 @@ object FastEvalEngineWorkflow {
         }
 
       val servingResult = (0 until evalQAsMap.size).map { ex =>
-        {
-          (evalInfoMap(ex), servingQPAMap(ex))
-        }
+        { (evalInfoMap(ex), servingQPAMap(ex)) }
       }.toSeq
 
       cache += Tuple2(prefix, servingResult)

repos/PredictionIO/core/src/main/scala/io/prediction/controller/LAlgorithm.scala

@@ -121,11 +121,7 @@ abstract class LAlgorithm[PD, M: ClassTag, Q, P]
       if (m.asInstanceOf[PersistentModel[Params]]
             .save(modelId, algoParams, sc)) {
         PersistentModelManifest(className = m.getClass.getName)
-      } else {
-        Unit
-      }
-    } else {
-      m
-    }
+      } else { Unit }
+    } else { m }
   }
 }

repos/PredictionIO/core/src/main/scala/io/prediction/controller/LServing.scala

@@ -36,9 +36,7 @@ abstract class LServing[Q, P] extends BaseServing[Q, P] {
   @Experimental
   def supplement(q: Q): Q = q
 
-  def serveBase(q: Q, ps: Seq[P]): P = {
-    serve(q, ps)
-  }
+  def serveBase(q: Q, ps: Seq[P]): P = { serve(q, ps) }
 
   /** Implement this method to combine multiple algorithms' predictions to
     * produce a single final prediction. The query is the original query sent to

repos/PredictionIO/core/src/main/scala/io/prediction/controller/P2LAlgorithm.scala

@@ -111,11 +111,7 @@ abstract class P2LAlgorithm[PD, M: ClassTag, Q: ClassTag, P]
       if (m.asInstanceOf[PersistentModel[Params]]
             .save(modelId, algoParams, sc)) {
         PersistentModelManifest(className = m.getClass.getName)
-      } else {
-        Unit
-      }
-    } else {
-      m
-    }
+      } else { Unit }
+    } else { m }
   }
 }

repos/PredictionIO/core/src/main/scala/io/prediction/controller/PAlgorithm.scala

@@ -115,11 +115,7 @@ abstract class PAlgorithm[PD, M, Q, P] extends BaseAlgorithm[PD, M, Q, P] {
       if (m.asInstanceOf[PersistentModel[Params]]
             .save(modelId, algoParams, sc)) {
         PersistentModelManifest(className = m.getClass.getName)
-      } else {
-        Unit
-      }
-    } else {
-      Unit
-    }
+      } else { Unit }
+    } else { Unit }
   }
 }

repos/PredictionIO/core/src/main/scala/io/prediction/controller/PPreparator.scala

@@ -28,9 +28,7 @@ import org.apache.spark.SparkContext
   */
 abstract class PPreparator[TD, PD] extends BasePreparator[TD, PD] {
 
-  def prepareBase(sc: SparkContext, td: TD): PD = {
-    prepare(sc, td)
-  }
+  def prepareBase(sc: SparkContext, td: TD): PD = { prepare(sc, td) }
 
   /** Implement this method to produce prepared data that is ready for model
     * training.

repos/PredictionIO/core/src/main/scala/io/prediction/controller/java/JavaEvaluation.scala

@@ -40,10 +40,7 @@ abstract class JavaEvaluation extends Evaluation {
     */
   def setEngineMetric[EI, Q, P, A](
       baseEngine: BaseEngine[EI, Q, P, A],
-      metric: Metric[EI, Q, P, A, _]) {
-
-    engineMetric = (baseEngine, metric)
-  }
+      metric: Metric[EI, Q, P, A, _]) { engineMetric = (baseEngine, metric) }
 
   /** Set the [[BaseEngine]] and [[Metric]]s for this [[JavaEvaluation]]
     *

repos/PredictionIO/core/src/main/scala/io/prediction/workflow/CoreWorkflow.scala

@@ -50,9 +50,7 @@ object CoreWorkflow {
 
     val batch = if (params.batch.nonEmpty) {
       s"{engineInstance.engineFactory} (${params.batch}})"
-    } else {
-      engineInstance.engineFactory
-    }
+    } else { engineInstance.engineFactory }
     val sc = WorkflowContext(batch, env, params.sparkEnv, mode.capitalize)
 
     try {
@@ -109,9 +107,7 @@ object CoreWorkflow {
 
     val batch = if (params.batch.nonEmpty) {
       s"{evaluation.getClass.getName} (${params.batch}})"
-    } else {
-      evaluation.getClass.getName
-    }
+    } else { evaluation.getClass.getName }
     val sc = WorkflowContext(batch, env, params.sparkEnv, mode.capitalize)
     val evaluationInstanceId = evaluationInstances.insert(evaluationInstance)
 

repos/PredictionIO/core/src/main/scala/io/prediction/workflow/CreateServer.scala

@@ -191,12 +191,8 @@ object CreateServer extends Logging {
           implicit val timeout = Timeout(5.seconds)
           master ? StartServer()
           actorSystem.awaitTermination
-        } getOrElse {
-          error(s"Invalid engine ID or version. Aborting server.")
-        }
-      } getOrElse {
-        error(s"Invalid engine instance ID. Aborting server.")
-      }
+        } getOrElse { error(s"Invalid engine ID or version. Aborting server.") }
+      } getOrElse { error(s"Invalid engine instance ID. Aborting server.") }
     }
   }
 
@@ -220,9 +216,7 @@ object CreateServer extends Logging {
 
     val batch = if (engineInstance.batch.nonEmpty) {
       s"${engineInstance.engineFactory} (${engineInstance.batch})"
-    } else {
-      engineInstance.engineFactory
-    }
+    } else { engineInstance.engineFactory }
 
     val sparkContext = WorkflowContext(
       batch = batch,
@@ -337,18 +331,14 @@ class MasterActor(
           interface = sc.ip,
           port = sc.port,
           settings = Some(settings.copy(sslEncryption = true)))
-      } getOrElse {
-        log.error("Cannot bind a non-existing server backend.")
-      }
+      } getOrElse { log.error("Cannot bind a non-existing server backend.") }
     case x: StopServer =>
       log.info(s"Stop server command received.")
       sprayHttpListener.map { l =>
         log.info("Server is shutting down.")
         l ! Http.Unbind(5.seconds)
         system.shutdown
-      } getOrElse {
-        log.warning("No active server is running.")
-      }
+      } getOrElse { log.warning("No active server is running.") }
     case x: ReloadServer =>
       log.info("Reload server command received.")
       val latestEngineInstance =
@@ -385,9 +375,7 @@ class MasterActor(
       if (retry > 0) {
         retry -= 1
         log.error(s"Bind failed. Retrying... ($retry more trial(s))")
-        context.system.scheduler.scheduleOnce(1.seconds) {
-          self ! BindServer()
-        }
+        context.system.scheduler.scheduleOnce(1.seconds) { self ! BindServer() }
       } else {
         log.error("Bind failed. Shutting down.")
         system.shutdown
@@ -459,9 +447,7 @@ class ServerActor[Q, P](
     if (args.accessKey.isEmpty) {
       log.error("Feedback loop cannot be enabled because accessKey is empty.")
       false
-    } else {
-      true
-    }
+    } else { true }
   } else false
 
   def remoteLog(logUrl: String, logPrefix: String, message: String): Unit = {
@@ -566,9 +552,7 @@ class ServerActor[Q, P](
                   implicit val formats =
                     algorithms.headOption map { alg =>
                       alg.querySerializer
-                    } getOrElse {
-                      Utils.json4sDefaultFormats
-                    }
+                    } getOrElse { Utils.json4sDefaultFormats }
                   // val genPrId = Random.alphanumeric.take(64).mkString
                   def genPrId: String = Random.alphanumeric.take(64).mkString
                   val newPrId = prediction match {
@@ -626,9 +610,7 @@ class ServerActor[Q, P](
                   // - if it is not WithPrId, no prId injection
                   if (prediction.isInstanceOf[WithPrId]) {
                     predictionJValue merge parse(s"""{"prId" : "$newPrId"}""")
-                  } else {
-                    predictionJValue
-                  }
+                  } else { predictionJValue }
                 } else predictionJValue
 
                 val pluginResult =
@@ -696,9 +678,7 @@ class ServerActor[Q, P](
           }
         }
       } ~
-      pathPrefix("assets") {
-        getFromResourceDirectory("assets")
-      } ~
+      pathPrefix("assets") { getFromResourceDirectory("assets") } ~
       path("plugins.json") {
         import EngineServerJson4sSupport._
         get {
@@ -738,9 +718,7 @@ class ServerActor[Q, P](
                 case EngineServerPlugin.outputSniffer =>
                   pluginsActorRef ? PluginsActor.HandleREST(
                     pluginName = pluginName,
-                    pluginArgs = pluginArgs) map {
-                    _.asInstanceOf[String]
-                  }
+                    pluginArgs = pluginArgs) map { _.asInstanceOf[String] }
               }
             }
           }

repos/PredictionIO/core/src/main/scala/io/prediction/workflow/CreateWorkflow.scala

@@ -133,9 +133,8 @@ object CreateWorkflow extends Logging {
     WorkflowUtils.modifyLogging(wfc.verbose)
 
     val evaluation = wfc.evaluationClass.map { ec =>
-      try {
-        WorkflowUtils.getEvaluation(ec, getClass.getClassLoader)._2
-      } catch {
+      try { WorkflowUtils.getEvaluation(ec, getClass.getClassLoader)._2 }
+      catch {
         case e @ (_: ClassNotFoundException | _: NoSuchMethodException) =>
           error(s"Unable to obtain evaluation $ec. Aborting workflow.", e)
           sys.exit(1)
@@ -187,9 +186,8 @@ object CreateWorkflow extends Logging {
           sys.exit(1)
       }
       val (engineLanguage, engineFactoryObj) =
-        try {
-          WorkflowUtils.getEngine(engineFactory, getClass.getClassLoader)
-        } catch {
+        try { WorkflowUtils.getEngine(engineFactory, getClass.getClassLoader) }
+        catch {
           case e @ (_: ClassNotFoundException | _: NoSuchMethodException) =>
             error(
               s"Unable to obtain engine: ${e.getMessage}. Aborting workflow.")
@@ -216,9 +214,7 @@ object CreateWorkflow extends Logging {
 
       val engineParams = if (wfc.engineParamsKey == "") {
         trainableEngine.jValueToEngineParams(variantJson, wfc.jsonExtractor)
-      } else {
-        engineFactoryObj.engineParams(wfc.engineParamsKey)
-      }
+      } else { engineFactoryObj.engineParams(wfc.engineParamsKey) }
 
       val engineInstance = EngineInstance(
         id = "",

repos/PredictionIO/core/src/main/scala/io/prediction/workflow/EngineServerPluginContext.scala

@@ -62,12 +62,8 @@ object EngineServerPluginContext extends Logging {
         if ((params \ "enabled").extractOrElse(false)) {
           info(s"Plugin ${service.pluginName} is enabled.")
           plugins(service.pluginType) += service.pluginName -> service
-        } else {
-          info(s"Plugin ${service.pluginName} is disabled.")
-        }
-      } getOrElse {
-        info(s"Plugin ${service.pluginName} is disabled.")
-      }
+        } else { info(s"Plugin ${service.pluginName} is disabled.") }
+      } getOrElse { info(s"Plugin ${service.pluginName} is disabled.") }
     }
     new EngineServerPluginContext(plugins, pluginParams, log)
   }

repos/PredictionIO/core/src/main/scala/io/prediction/workflow/FakeWorkflow.scala

@@ -99,7 +99,5 @@ trait FakeRun extends Evaluation with EngineParamsGenerator {
   }
 
   def func: (SparkContext => Unit) = { (sc: SparkContext) => Unit }
-  def func_=(f: SparkContext => Unit) {
-    runner = new FakeRunner(f)
-  }
+  def func_=(f: SparkContext => Unit) { runner = new FakeRunner(f) }
 }

repos/PredictionIO/core/src/main/scala/io/prediction/workflow/JsonExtractor.scala

@@ -63,9 +63,8 @@ object JsonExtractor {
 
     extractorOption match {
       case JsonExtractorOption.Both =>
-        try {
-          extractWithJson4sNative(json, json4sFormats, clazz)
-        } catch {
+        try { extractWithJson4sNative(json, json4sFormats, clazz) }
+        catch {
           case e: Exception =>
             extractWithGson(json, clazz, gsonTypeAdapterFactories)
         }