add style check for java and scala code

jvm-packages/xgboost4j/src/main/scala/org/dmlc/xgboost4j/scala/Booster.scala

@@ -1,3 +1,19 @@
+/*
+ Copyright (c) 2014 by Contributors
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ */
+
 package org.dmlc.xgboost4j.scala
 
 import java.io.IOException
@@ -111,10 +127,10 @@ trait Booster {
    *
    * @param data      dmatrix storing the input
    * @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
-   * @param predLeaf  When this option is on, the output will be a matrix of (nsample, ntrees), nsample = data.numRow
-  with each record indicating the predicted leaf index of each sample in each tree.
-  Note that the leaf index of a tree is unique per tree, so you may find leaf 1
-  in both tree 1 and tree 0.
+   * @param predLeaf  When this option is on, the output will be a matrix of (nsample, ntrees),
+   *                  nsample = data.numRow with each record indicating the predicted leaf index of
+   *                  each sample in each tree. Note that the leaf index of a tree is unique per
+   *                  tree, so you may find leaf 1 in both tree 1 and tree 0.
    * @return predict result
    * @throws XGBoostError native error
    */

jvm-packages/xgboost4j/src/main/scala/org/dmlc/xgboost4j/scala/DMatrix.scala

@@ -1,3 +1,19 @@
+/*
+ Copyright (c) 2014 by Contributors
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ */
+
 package org.dmlc.xgboost4j.scala
 
 import org.dmlc.xgboost4j.{DMatrix => JDMatrix, XGBoostError}

jvm-packages/xgboost4j/src/main/scala/org/dmlc/xgboost4j/scala/EvalTrait.scala

@@ -0,0 +1,38 @@
+/*
+ Copyright (c) 2014 by Contributors
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ */
+
+package org.dmlc.xgboost4j.scala
+
+import org.dmlc.xgboost4j.IEvaluation
+
+trait EvalTrait extends IEvaluation {
+
+  /**
+   * get evaluate metric
+   *
+   * @return evalMetric
+   */
+  def getMetric: String
+
+  /**
+   * evaluate with predicts and data
+   *
+   * @param predicts predictions as array
+   * @param dmat     data matrix to evaluate
+   * @return result of the metric
+   */
+  def eval(predicts: Array[Array[Float]], dmat: DMatrix): Float
+}

jvm-packages/xgboost4j/src/main/scala/org/dmlc/xgboost4j/scala/ObjectiveTrait.scala

@@ -0,0 +1,30 @@
+/*
+ Copyright (c) 2014 by Contributors
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ */
+
+package org.dmlc.xgboost4j.scala
+
+import org.dmlc.xgboost4j.IObjective
+
+trait ObjectiveTrait extends IObjective {
+  /**
+   * user define objective function, return gradient and second order gradient
+   *
+   * @param predicts untransformed margin predicts
+   * @param dtrain   training data
+   * @return List with two float array, correspond to first order grad and second order grad
+   */
+  def getGradient(predicts: Array[Array[Float]], dtrain: DMatrix): java.util.List[Array[Float]]
+}

jvm-packages/xgboost4j/src/main/scala/org/dmlc/xgboost4j/scala/ScalaBoosterImpl.scala

@@ -1,3 +1,19 @@
+/*
+ Copyright (c) 2014 by Contributors
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ */
+
 package org.dmlc.xgboost4j.scala
 
 import scala.collection.JavaConverters._
@@ -35,7 +51,8 @@ private[scala] class ScalaBoosterImpl private[xgboost4j](booster: JBooster) exte
     booster.evalSet(evalMatrixs.map(_.jDMatrix), evalNames, iter)
   }
 
-  override def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], eval: IEvaluation): String = {
+  override def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], eval: IEvaluation):
+      String = {
     booster.evalSet(evalMatrixs.map(_.jDMatrix), evalNames, eval)
   }
 
@@ -51,7 +68,8 @@ private[scala] class ScalaBoosterImpl private[xgboost4j](booster: JBooster) exte
     booster.predict(data.jDMatrix, outPutMargin)
   }
 
-  override def predict(data: DMatrix, outPutMargin: Boolean, treeLimit: Int): Array[Array[Float]] = {
+  override def predict(data: DMatrix, outPutMargin: Boolean, treeLimit: Int):
+      Array[Array[Float]] = {
     booster.predict(data.jDMatrix, outPutMargin, treeLimit)
   }
 

jvm-packages/xgboost4j/src/main/scala/org/dmlc/xgboost4j/scala/XGBoost.scala

@@ -1,30 +1,47 @@
+/*
+ Copyright (c) 2014 by Contributors
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ */
+
 package org.dmlc.xgboost4j.scala
 
 import _root_.scala.collection.JavaConverters._
-
-import org.dmlc.xgboost4j
-import org.dmlc.xgboost4j.{XGBoost => JXGBoost, IEvaluation, IObjective}
+import org.dmlc.xgboost4j.{IEvaluation, IObjective, XGBoost => JXGBoost}
 
 object XGBoost {
 
-  def train(params: Map[String, AnyRef], dtrain: xgboost4j.DMatrix, round: Int,
-            watches: Map[String, xgboost4j.DMatrix], obj: IObjective, eval: IEvaluation): Booster = {
-    val xgboostInJava = JXGBoost.train(params.asJava, dtrain, round, watches.asJava, obj, eval)
+  def train(params: Map[String, AnyRef], dtrain: DMatrix, round: Int,
+            watches: Map[String, DMatrix], obj: IObjective, eval: IEvaluation): Booster = {
+    val jWatches = watches.map{case (name, matrix) => (name, matrix.jDMatrix)}
+    val xgboostInJava = JXGBoost.train(params.asJava, dtrain.jDMatrix, round, jWatches.asJava,
+      obj, eval)
     new ScalaBoosterImpl(xgboostInJava)
   }
 
-  def crossValiation(params: Map[String, AnyRef],
-                     data: DMatrix,
-                     round: Int,
-                     nfold: Int,
-                     metrics: Array[String],
-                     obj: IObjective,
-                     eval: IEvaluation): Array[String] = {
-    JXGBoost.crossValiation(params.asJava, data.jDMatrix, round, nfold, metrics, obj,
-      eval)
+  def crossValiation(
+      params: Map[String, AnyRef],
+      data: DMatrix,
+      round: Int,
+      nfold: Int,
+      metrics: Array[String],
+      obj: EvalTrait,
+      eval: ObjectiveTrait): Array[String] = {
+    JXGBoost.crossValiation(params.asJava, data.jDMatrix, round, nfold, metrics,
+      obj.asInstanceOf[IObjective], eval.asInstanceOf[IEvaluation])
   }
 
-  def initBoostModel(params: Map[String, AnyRef],  dMatrixs: Array[DMatrix]): Booster = {
+  def initBoostModel(params: Map[String, AnyRef], dMatrixs: Array[DMatrix]): Booster = {
     val xgboostInJava = JXGBoost.initBoostingModel(params.asJava, dMatrixs.map(_.jDMatrix))
     new ScalaBoosterImpl(xgboostInJava)
   }