made the isClassification parameter for the check numeric types metho…

…d optional
apache · May 12, 2016 · ce19549 · ce19549
1 parent a8e5aa0
commit ce19549
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Showing 17 changed files with 17 additions and 18 deletions.
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala
@@ -337,7 +337,7 @@ class DecisionTreeClassifierSuite
   test("should support all NumericType labels and not support other types") {
     val dt = new DecisionTreeClassifier().setMaxDepth(1)
     MLTestingUtils.checkNumericTypes[DecisionTreeClassificationModel, DecisionTreeClassifier](
-      dt, isClassification = true, spark) { (expected, actual) =>
+      dt, spark) { (expected, actual) =>
         TreeTests.checkEqual(expected, actual)
       }
   }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala
@@ -106,7 +106,7 @@ class GBTClassifierSuite extends SparkFunSuite with MLlibTestSparkContext
   test("should support all NumericType labels and not support other types") {
     val gbt = new GBTClassifier().setMaxDepth(1)
     MLTestingUtils.checkNumericTypes[GBTClassificationModel, GBTClassifier](
-      gbt, isClassification = true, spark) { (expected, actual) =>
+      gbt, spark) { (expected, actual) =>
         TreeTests.checkEqual(expected, actual)
       }
   }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
@@ -938,7 +938,7 @@ class LogisticRegressionSuite
   test("should support all NumericType labels and not support other types") {
     val lr = new LogisticRegression().setMaxIter(1)
     MLTestingUtils.checkNumericTypes[LogisticRegressionModel, LogisticRegression](
-      lr, isClassification = true, spark) { (expected, actual) =>
+      lr, spark) { (expected, actual) =>
         assert(expected.intercept === actual.intercept)
         assert(expected.coefficients.toArray === actual.coefficients.toArray)
       }

diff --git a/...c/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala b/...c/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala
@@ -169,7 +169,7 @@ class MultilayerPerceptronClassifierSuite
     val mpc = new MultilayerPerceptronClassifier().setLayers(layers).setMaxIter(1)
     MLTestingUtils.checkNumericTypes[
         MultilayerPerceptronClassificationModel, MultilayerPerceptronClassifier](
-      mpc, isClassification = true, spark) { (expected, actual) =>
+      mpc, spark) { (expected, actual) =>
         assert(expected.layers === actual.layers)
         assert(expected.weights === actual.weights)
       }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala
@@ -188,7 +188,7 @@ class NaiveBayesSuite extends SparkFunSuite with MLlibTestSparkContext with Defa
   test("should support all NumericType labels and not support other types") {
     val nb = new NaiveBayes()
     MLTestingUtils.checkNumericTypes[NaiveBayesModel, NaiveBayes](
-      nb, isClassification = true, spark) { (expected, actual) =>
+      nb, spark) { (expected, actual) =>
         assert(expected.pi === actual.pi)
         assert(expected.theta === actual.theta)
       }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala
@@ -228,7 +228,7 @@ class OneVsRestSuite extends SparkFunSuite with MLlibTestSparkContext with Defau
   test("should support all NumericType labels and not support other types") {
     val ovr = new OneVsRest().setClassifier(new LogisticRegression().setMaxIter(1))
     MLTestingUtils.checkNumericTypes[OneVsRestModel, OneVsRest](
-      ovr, isClassification = true, spark) { (expected, actual) =>
+      ovr, spark) { (expected, actual) =>
         val expectedModels = expected.models.map(m => m.asInstanceOf[LogisticRegressionModel])
         val actualModels = actual.models.map(m => m.asInstanceOf[LogisticRegressionModel])
         assert(expectedModels.length === actualModels.length)

diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala
@@ -189,7 +189,7 @@ class RandomForestClassifierSuite
   test("should support all NumericType labels and not support other types") {
     val rf = new RandomForestClassifier().setMaxDepth(1)
     MLTestingUtils.checkNumericTypes[RandomForestClassificationModel, RandomForestClassifier](
-      rf, isClassification = true, spark) { (expected, actual) =>
+      rf, spark) { (expected, actual) =>
         TreeTests.checkEqual(expected, actual)
       }
   }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala
@@ -85,7 +85,7 @@ class ChiSqSelectorSuite extends SparkFunSuite with MLlibTestSparkContext
   test("should support all NumericType labels and not support other types") {
     val css = new ChiSqSelector()
     MLTestingUtils.checkNumericTypes[ChiSqSelectorModel, ChiSqSelector](
-      css, isClassification = true, sqlContext) { (expected, actual) =>
+      css, sqlContext) { (expected, actual) =>
         assert(expected.selectedFeatures === actual.selectedFeatures)
       }
   }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala
@@ -134,7 +134,6 @@ class RFormulaSuite extends SparkFunSuite with MLlibTestSparkContext with Defaul
     ).toDF("id", "a", "b")
     val model = formula.fit(original)
     val result = model.transform(original)
-    val resultSchema = model.transformSchema(original.schema)
     val expected = spark.createDataFrame(
       Seq(
         ("male", "foo", 4, Vectors.dense(0.0, 1.0, 4.0), 1.0),

diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
@@ -356,7 +356,7 @@ class AFTSurvivalRegressionSuite
   test("should support all NumericType labels") {
     val aft = new AFTSurvivalRegression().setMaxIter(1)
     MLTestingUtils.checkNumericTypes[AFTSurvivalRegressionModel, AFTSurvivalRegression](
-      aft, isClassification = false, spark) { (expected, actual) =>
+      aft, spark, isClassification = false) { (expected, actual) =>
         assert(expected.intercept === actual.intercept)
         assert(expected.coefficients === actual.coefficients)
       }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala
@@ -120,7 +120,7 @@ class DecisionTreeRegressorSuite
   test("should support all NumericType labels and not support other types") {
     val dt = new DecisionTreeRegressor().setMaxDepth(1)
     MLTestingUtils.checkNumericTypes[DecisionTreeRegressionModel, DecisionTreeRegressor](
-      dt, isClassification = false, spark) { (expected, actual) =>
+      dt, spark, isClassification = false) { (expected, actual) =>
         TreeTests.checkEqual(expected, actual)
       }
   }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala
@@ -115,7 +115,7 @@ class GBTRegressorSuite extends SparkFunSuite with MLlibTestSparkContext
   test("should support all NumericType labels and not support other types") {
     val gbt = new GBTRegressor().setMaxDepth(1)
     MLTestingUtils.checkNumericTypes[GBTRegressionModel, GBTRegressor](
-      gbt, isClassification = false, spark) { (expected, actual) =>
+      gbt, spark, isClassification = false) { (expected, actual) =>
         TreeTests.checkEqual(expected, actual)
       }
   }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
@@ -1021,7 +1021,7 @@ class GeneralizedLinearRegressionSuite
     val glr = new GeneralizedLinearRegression().setMaxIter(1)
     MLTestingUtils.checkNumericTypes[
         GeneralizedLinearRegressionModel, GeneralizedLinearRegression](
-      glr, isClassification = false, spark) { (expected, actual) =>
+      glr, spark, isClassification = false) { (expected, actual) =>
         assert(expected.intercept === actual.intercept)
         assert(expected.coefficients === actual.coefficients)
       }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala
@@ -184,7 +184,7 @@ class IsotonicRegressionSuite
   test("should support all NumericType labels and not support other types") {
     val ir = new IsotonicRegression()
     MLTestingUtils.checkNumericTypes[IsotonicRegressionModel, IsotonicRegression](
-      ir, isClassification = false, spark) { (expected, actual) =>
+      ir, spark, isClassification = false) { (expected, actual) =>
         assert(expected.boundaries === actual.boundaries)
         assert(expected.predictions === actual.predictions)
       }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala
@@ -1010,7 +1010,7 @@ class LinearRegressionSuite
   test("should support all NumericType labels and not support other types") {
     val lr = new LinearRegression().setMaxIter(1)
     MLTestingUtils.checkNumericTypes[LinearRegressionModel, LinearRegression](
-      lr, isClassification = false, spark) { (expected, actual) =>
+      lr, spark, isClassification = false) { (expected, actual) =>
         assert(expected.intercept === actual.intercept)
         assert(expected.coefficients === actual.coefficients)
       }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala
@@ -98,7 +98,7 @@ class RandomForestRegressorSuite extends SparkFunSuite with MLlibTestSparkContex
   test("should support all NumericType labels and not support other types") {
     val rf = new RandomForestRegressor().setMaxDepth(1)
     MLTestingUtils.checkNumericTypes[RandomForestRegressionModel, RandomForestRegressor](
-      rf, isClassification = false, spark) { (expected, actual) =>
+      rf, spark, isClassification = false) { (expected, actual) =>
         TreeTests.checkEqual(expected, actual)
       }
   }

diff --git a/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala b/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala
@@ -37,8 +37,8 @@ object MLTestingUtils extends SparkFunSuite {
 
   def checkNumericTypes[M <: Model[M], T <: Estimator[M]](
       estimator: T,
-      isClassification: Boolean,
-      spark: SparkSession)(check: (M, M) => Unit): Unit = {
+      spark: SparkSession,
+      isClassification: Boolean = true)(check: (M, M) => Unit): Unit = {
     val dfs = if (isClassification) {
       genClassifDFWithNumericLabelCol(spark)
     } else {