add test cases for Scala API

jvm-packages/pom.xml

@@ -95,13 +95,25 @@
                 <groupId>org.apache.maven.plugins</groupId>
                 <artifactId>maven-surefire-plugin</artifactId>
                 <version>2.19.1</version>
-                <configuration>
-                    <argLine>-Djava.library.path=lib/</argLine>
-                </configuration>
             </plugin>
         </plugins>
     </build>
     <dependencies>
+        <dependency>
+            <groupId>org.scala-lang</groupId>
+            <artifactId>scala-compiler</artifactId>
+            <version>${scala.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>org.scala-lang</groupId>
+            <artifactId>scala-reflect</artifactId>
+            <version>${scala.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>org.scala-lang</groupId>
+            <artifactId>scala-library</artifactId>
+            <version>${scala.version}</version>
+        </dependency>
         <dependency>
             <groupId>commons-logging</groupId>
             <artifactId>commons-logging</artifactId>
@@ -113,5 +125,10 @@
             <version>2.2.6</version>
             <scope>test</scope>
         </dependency>
+        <dependency>
+            <groupId>com.typesafe</groupId>
+            <artifactId>config</artifactId>
+            <version>1.3.0</version>
+        </dependency>
     </dependencies>
 </project>

jvm-packages/scalastyle-config.xml

@@ -134,21 +134,6 @@ This file is divided into 3 sections:
   <!-- ??? usually shouldn't be checked into the code base. -->
   <check level="error" class="org.scalastyle.scalariform.NotImplementedErrorUsage" enabled="true"></check>
 
-  <!-- As of SPARK-7558, all tests in Spark should extend o.a.s.SparkFunSuite instead of FunSuite directly -->
-  <check customId="funsuite" level="error" class="org.scalastyle.scalariform.TokenChecker" enabled="true">
-    <parameters><parameter name="regex">^FunSuite[A-Za-z]*$</parameter></parameters>
-    <customMessage>Tests must extend org.apache.spark.SparkFunSuite instead.</customMessage>
-  </check>
-
-  <!-- As of SPARK-7977 all printlns need to be wrapped in '// scalastyle:off/on println' -->
-  <check customId="println" level="error" class="org.scalastyle.scalariform.TokenChecker" enabled="true">
-    <parameters><parameter name="regex">^println$</parameter></parameters>
-    <customMessage><![CDATA[Are you sure you want to println? If yes, wrap the code block with
-      // scalastyle:off println
-      println(...)
-      // scalastyle:on println]]></customMessage>
-  </check>
-
   <check customId="visiblefortesting" level="error" class="org.scalastyle.file.RegexChecker" enabled="true">
     <parameters><parameter name="regex">@VisibleForTesting</parameter></parameters>
     <customMessage><![CDATA[

jvm-packages/xgboost4j/pom.xml

@@ -22,6 +22,19 @@
                     <nohelp>true</nohelp>
                 </configuration>
             </plugin>
+            <plugin>
+                <groupId>org.scalatest</groupId>
+                <artifactId>scalatest-maven-plugin</artifactId>
+                <version>1.0</version>
+                <executions>
+                    <execution>
+                        <id>test</id>
+                        <goals>
+                            <goal>test</goal>
+                        </goals>
+                    </execution>
+                </executions>
+            </plugin>
         </plugins>
     </build>
     <dependencies>

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

@@ -18,7 +18,7 @@ package ml.dmlc.xgboost4j.scala
 
 import ml.dmlc.xgboost4j.{DMatrix => JDMatrix, XGBoostError}
 
-class DMatrix private(private[scala] val jDMatrix: JDMatrix) {
+class DMatrix private[scala](private[scala] val jDMatrix: JDMatrix) {
 
   /**
    * init DMatrix from file (svmlight format)

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

@@ -16,7 +16,7 @@
 
 package ml.dmlc.xgboost4j.scala
 
-import ml.dmlc.xgboost4j.IEvaluation
+import ml.dmlc.xgboost4j.{DMatrix => JDMatrix, IEvaluation}
 
 trait EvalTrait extends IEvaluation {
 
@@ -35,4 +35,8 @@ trait EvalTrait extends IEvaluation {
    * @return result of the metric
    */
   def eval(predicts: Array[Array[Float]], dmat: DMatrix): Float
+
+  private[scala] def eval(predicts: Array[Array[Float]], jdmat: JDMatrix): Float = {
+    eval(predicts, new DMatrix(jdmat))
+  }
 }

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

@@ -16,7 +16,9 @@
 
 package ml.dmlc.xgboost4j.scala
 
-import ml.dmlc.xgboost4j.IObjective
+import scala.collection.JavaConverters._
+
+import ml.dmlc.xgboost4j.{DMatrix => JDMatrix, IObjective}
 
 trait ObjectiveTrait extends IObjective {
   /**
@@ -26,5 +28,10 @@ trait ObjectiveTrait extends IObjective {
    * @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]]
+  def getGradient(predicts: Array[Array[Float]], dtrain: DMatrix): List[Array[Float]]
+
+  private[scala] def getGradient(predicts: Array[Array[Float]], dtrain: JDMatrix):
+    java.util.List[Array[Float]] = {
+    getGradient(predicts, new DMatrix(dtrain)).asJava
+  }
 }

jvm-packages/xgboost4j/src/test/java/ml/dmlc/xgboost4j/BoosterImplTest.java

@@ -80,7 +80,7 @@ public class BoosterImplTest {
     };
 
     //set watchList
-    HashMap<String, DMatrix> watches = new HashMap<>();
+    HashMap<String, DMatrix> watches = new HashMap<String, DMatrix>();
 
     watches.put("train", trainMat);
     watches.put("test", testMat);
@@ -129,10 +129,6 @@ public class BoosterImplTest {
     //do 5-fold cross validation
     int round = 2;
     int nfold = 5;
-    //set additional eval_metrics
+    String[] evalHist = XGBoost.crossValiation(param, trainMat, round, nfold, null, null, null);
-    String[] metrics = null;
-
-    String[] evalHist = XGBoost.crossValiation(param, trainMat, round, nfold, metrics,
-            null, null);
   }
 }

jvm-packages/xgboost4j/src/test/java/ml/dmlc/xgboost4j/DMatrixTest.java

@@ -57,7 +57,6 @@ public class DMatrixTest {
     long[] rowHeaders = new long[]{0, 3, 7, 11};
     DMatrix dmat1 = new DMatrix(rowHeaders, colIndex, data, DMatrix.SparseType.CSR);
     //check row num
-    System.out.println(dmat1.rowNum());
     TestCase.assertTrue(dmat1.rowNum() == 3);
     //test set label
     float[] label1 = new float[]{1, 0, 1};

jvm-packages/xgboost4j/src/test/scala/ml/dmlc/xgboost4j/scala/DMatrixSuite.scala

@@ -0,0 +1,85 @@
+/*
+ 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 ml.dmlc.xgboost4j.scala
+
+import java.util.Arrays
+
+import scala.util.Random
+
+import ml.dmlc.xgboost4j.{DMatrix => JDMatrix}
+import org.scalatest.FunSuite
+
+class DMatrixSuite extends FunSuite {
+  test("create DMatrix from File") {
+    val dmat = new DMatrix("../../demo/data/agaricus.txt.test")
+    // get label
+    val labels: Array[Float] = dmat.getLabel
+    // check length
+    assert(dmat.rowNum === labels.length)
+    // set weights
+    val weights: Array[Float] = Arrays.copyOf(labels, labels.length)
+    dmat.setWeight(weights)
+    val dweights: Array[Float] = dmat.getWeight
+    assert(weights === dweights)
+  }
+
+  test("create DMatrix from CSR") {
+    // create Matrix from csr format sparse Matrix and labels
+    /**
+     * sparse matrix
+     * 1 0 2 3 0
+     * 4 0 2 3 5
+     * 3 1 2 5 0
+     */
+    val data = List[Float](1, 2, 3, 4, 2, 3, 5, 3, 1, 2, 5).toArray
+    val colIndex = List(0, 2, 3, 0, 2, 3, 4, 0, 1, 2, 3).toArray
+    val rowHeaders = List[Long](0, 3, 7, 11).toArray
+    val dmat1 = new DMatrix(rowHeaders, colIndex, data, JDMatrix.SparseType.CSR)
+    assert(dmat1.rowNum === 3)
+    val label1 = List[Float](1, 0, 1).toArray
+    dmat1.setLabel(label1)
+    val label2 = dmat1.getLabel
+    assert(label2 === label1)
+  }
+
+  test("create DMatrix from DenseMatrix") {
+    val nrow = 10
+    val ncol = 5
+    val data0 = new Array[Float](nrow * ncol)
+    // put random nums
+    for (i <- data0.indices) {
+      data0(i) = Random.nextFloat()
+    }
+    // create label
+    val label0 = new Array[Float](nrow)
+    for (i <- label0.indices) {
+      label0(i) = Random.nextFloat()
+    }
+    val dmat0 = new DMatrix(data0, nrow, ncol)
+    dmat0.setLabel(label0)
+    // check
+    assert(dmat0.rowNum === 10)
+    assert(dmat0.getLabel.length === 10)
+    // set weights for each instance
+    val weights = new Array[Float](nrow)
+    for (i <- weights.indices) {
+      weights(i) = Random.nextFloat()
+    }
+    dmat0.setWeight(weights)
+    assert(weights === dmat0.getWeight)
+  }
+}

jvm-packages/xgboost4j/src/test/scala/ml/dmlc/xgboost4j/scala/ScalaBoosterImplSuite.scala

@@ -0,0 +1,90 @@
+/*
+ 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 ml.dmlc.xgboost4j.scala
+
+import ml.dmlc.xgboost4j.XGBoostError
+import org.apache.commons.logging.LogFactory
+import org.scalatest.FunSuite
+
+class ScalaBoosterImplSuite extends FunSuite {
+
+  private class EvalError extends EvalTrait {
+
+    val logger = LogFactory.getLog(classOf[EvalError])
+
+    private[xgboost4j] var evalMetric: String = "custom_error"
+
+    /**
+     * get evaluate metric
+     *
+     * @return evalMetric
+     */
+    override def getMetric: String = evalMetric
+
+    /**
+     * evaluate with predicts and data
+     *
+     * @param predicts predictions as array
+     * @param dmat     data matrix to evaluate
+     * @return result of the metric
+     */
+    override def eval(predicts: Array[Array[Float]], dmat: DMatrix): Float = {
+      var error: Float = 0f
+      var labels: Array[Float] = null
+      try {
+        labels = dmat.getLabel
+      } catch {
+        case ex: XGBoostError =>
+          logger.error(ex)
+          return -1f
+      }
+      val nrow: Int = predicts.length
+      for (i <- 0 until nrow) {
+        if (labels(i) == 0.0 && predicts(i)(0) > 0) {
+          error += 1
+        } else if (labels(i) == 1.0 && predicts(i)(0) <= 0) {
+          error += 1
+        }
+      }
+      error / labels.length
+    }
+  }
+
+  test("basic operation of booster") {
+    val trainMat = new DMatrix("../../demo/data/agaricus.txt.train")
+    val testMat = new DMatrix("../../demo/data/agaricus.txt.test")
+
+    val paramMap = List("eta" -> "1", "max_depth" -> "2", "silent" -> "1",
+      "objective" -> "binary:logistic").toMap
+    val watches = List("train" -> trainMat, "test" -> testMat).toMap
+
+    val round = 2
+    val booster = XGBoost.train(paramMap, trainMat, round, watches, null, null)
+    val predicts = booster.predict(testMat, true)
+    val eval = new EvalError
+    assert(eval.eval(predicts, testMat) < 0.1)
+  }
+
+  test("cross validation") {
+    val trainMat = new DMatrix("../../demo/data/agaricus.txt.train")
+    val params = List("eta" -> "1.0", "max_depth" -> "3", "slient" -> "1", "nthread" -> "6",
+      "objective" -> "binary:logistic", "gamma" -> "1.0", "eval_metric" -> "error").toMap
+    val round = 2
+    val nfold = 5
+    XGBoost.crossValiation(params, trainMat, round, nfold, null, null, null)
+  }
+}