Cleaning up tests per PR comments

core/src/test/scala/com/salesforce/op/ModelInsightsTest.scala

@@ -576,7 +576,7 @@ class ModelInsightsTest extends FlatSpec with PassengerSparkFixtureTest with Dou
  },
  Seq("f1", "f0").map(name => name -> FeatureHistory(originFeatures = Seq(name), stages = Seq())).toMap,
  Map(
- "f0" -> Seq(SensitiveNameInformation(0.0, Seq.empty[GenderDetectionResults], 0.0, 0.0, 1.0, "f0", None, false))
+ "f0" -> Seq(SensitiveNameInformation(0.0, Seq.empty[GenderDetectionResults], 0.0, 0.0, 1.0, "f0", None))
  )
  )
 
@@ -709,32 +709,33 @@ class ModelInsightsTest extends FlatSpec with PassengerSparkFixtureTest with Dou
  """include sensitive feature information
  |even for sensitive features that are removed from output vector and output vector metadata""".stripMargin in {
  // Copy metadata from above but add new feature that was removed in vectorizing to sensitive info
- val f_notInMeta = Feature[Text]("f_notInMeta", false, null, Seq(), "test")
- val newMeta = OpVectorMetadata(
- "fv",
+ val f_notInMeta = Feature[Text]("f_notInMeta", isResponse = false, null, Seq(), "test")
+ val newFeatureName = "fv"
+ val newColumnMeta = OpVectorColumnMetadata(
+ parentFeatureName = Seq("f1"),
+ parentFeatureType = Seq(classOf[Real].getName),
+ grouping = None,
+ indicatorValue = None
+ ) +: Array("f2", "f3").map { name =>
  OpVectorColumnMetadata(
- parentFeatureName = Seq("f1"),
- parentFeatureType = Seq(classOf[Real].getName),
- grouping = None,
- indicatorValue = None
- ) +: Array("f2", "f3").map { name =>
- OpVectorColumnMetadata(
- parentFeatureName = Seq("f0"),
- parentFeatureType = Seq(classOf[PickList].getName),
- grouping = Option("f0"),
- indicatorValue = Option(name)
- )
- },
- Seq("f1", "f0").map(name => name -> FeatureHistory(originFeatures = Seq(name), stages = Seq())).toMap,
- Map(
- "f0" -> Seq(SensitiveNameInformation(
- 0.0, Seq.empty[GenderDetectionResults], 0.0, 0.0, 1.0, "f0", None, false
- )),
- "f_notInMeta" -> Seq(SensitiveNameInformation(
- 1.0, Seq.empty[GenderDetectionResults], 0.0, 0.0, 1.0, "f_notInMeta", None, true
- ))
+ parentFeatureName = Seq("f0"),
+ parentFeatureType = Seq(classOf[PickList].getName),
+ grouping = Option("f0"),
+ indicatorValue = Option(name)
  )
+ }
+ val newFeatureHistory = Seq("f1", "f0").map(
+ name => name -> FeatureHistory(originFeatures = Seq(name), stages = Seq())
+ ).toMap
+ val newSensitiveInfo = Map(
+ "f0" -> Seq(SensitiveNameInformation(
+ 0.0, Seq.empty[GenderDetectionResults], 0.0, 0.0, 1.0, "f0", None
+ )),
+ "f_notInMeta" -> Seq(SensitiveNameInformation(
+ 1.0, Seq.empty[GenderDetectionResults], 0.0, 0.0, 1.0, "f_notInMeta", None, actionTaken = true
+ ))
  )
+ val newMeta = OpVectorMetadata(newFeatureName, newColumnMeta, newFeatureHistory, newSensitiveInfo)
 
  val labelSum = ModelInsights.getLabelSummary(Option(lbl), Option(summary))
 
@@ -749,7 +750,7 @@ class ModelInsightsTest extends FlatSpec with PassengerSparkFixtureTest with Dou
  f_notInMeta_butInInsights.derivedFeatures.size shouldBe 0
  f_notInMeta_butInInsights.sensitiveInformation match {
  case Seq(SensitiveNameInformation(
- probName, genderDetectResults, probMale, probFemale, probOther, name, mapKey, actionTaken
+ probName, genderDetectResults, probMale, probFemale, probOther, _, _, actionTaken
  )) =>
  actionTaken shouldBe true
  probName shouldBe 1.0

features/src/test/scala/com/salesforce/op/utils/spark/OPVectorMetadataTest.scala

@@ -76,7 +76,7 @@ class OPVectorMetadataTest extends PropSpec with TestCommon with PropertyChecks
  )
  val arrVecColTupleGen: Gen[Array[OpVectorColumnTuple]] = Gen.containerOf[Array, OpVectorColumnTuple](vecColTupleGen)
 
- val sensitiveGen: Gen[SensitiveTuple] = for {
+ val sensitiveNameGen: Gen[SensitiveTuple] = for {
  featureName <- genName
  mapKey <- Gen.option(genName)
  actionTaken <- Gen.oneOf[Boolean](Seq(false, true))
@@ -94,7 +94,7 @@ class OPVectorMetadataTest extends PropSpec with TestCommon with PropertyChecks
  name <- genName
  arr <- arrVecColTupleGen
  histories <- featHistTupleGen
- sensitiveCols <- Gen.containerOf[Seq, SensitiveTuple](sensitiveGen)
+ sensitiveCols <- Gen.containerOf[Seq, SensitiveTuple](sensitiveNameGen)
  } yield {
  (name, arr, histories, sensitiveCols)
  }