REFACTOR: Update reproducibility test case to reflect changes (#237)

src/test/scala/au/csiro/variantspark/misc/ReproducibilityTest.scala

@@ -6,7 +6,8 @@ import org.junit.Test
 import org.junit.Ignore
 import org.junit.Assert._
 import au.csiro.variantspark.api._
-import org.apache.spark.sql.SparkSession
+import au.csiro.variantspark.algo.RandomForestParams
+import org.apache.spark.sql.{SparkSession, SQLContext}
 import org.apache.spark.SparkConf
 
 /**
@@ -21,18 +22,20 @@ class ReproducibilityTest extends SparkTest {
     .getOrCreate()
 
   @Test
-  @Ignore
   def testReproducibleResults() {
     implicit val vsContext = VSContext(spark)
+    implicit val sqlContext = spark.sqlContext
     val features = vsContext.importVCF("data/chr22_1000.vcf", 3)
     val label = vsContext.loadLabel("data/chr22-labels.csv", "22_16051249")
-    val impAnalysis1 = features.importanceAnalysis(label, nTrees = 40, seed = Some(13L),
-      mtryFraction = None, batchSize = 20)
-    val topVariables1 = impAnalysis1.importantVariables(20)
+    val params = RandomForestParams(seed = 13L)
+    val rfModel1 = RFModelTrainer.trainModel(features, label, params, 40, 20)
+    val impAnalysis1 = new ImportanceAnalysis(sqlContext, features, rfModel1)
+    val topVariables1 = impAnalysis1.importantVariables(20, false)
     topVariables1.foreach(println)
-    val impAnalysis2 = features.importanceAnalysis(label, nTrees = 40, seed = Some(13L),
-      mtryFraction = None, batchSize = 20)
-    val topVariables2 = impAnalysis2.importantVariables(20)
+    println()
+    val rfModel2 = RFModelTrainer.trainModel(features, label, params, 40, 20)
+    val impAnalysis2 = new ImportanceAnalysis(sqlContext, features, rfModel2)
+    val topVariables2 = impAnalysis2.importantVariables(20, false)
     topVariables2.foreach(println)
     topVariables1.zip(topVariables2).foreach { p => assertEquals(p._1, p._2) }
   }