try sparse vector clone for test fix

core/src/main/scala/com/salesforce/op/stages/impl/insights/RecordInsightsLOCO.scala

@@ -37,7 +37,7 @@ import com.salesforce.op.stages.impl.feature.TimePeriod
 import com.salesforce.op.stages.impl.selector.SelectedModel
 import com.salesforce.op.stages.sparkwrappers.specific.OpPredictorWrapperModel
 import com.salesforce.op.stages.sparkwrappers.specific.SparkModelConverter._
-import com.salesforce.op.utils.spark.RichVector._
+import com.salesforce.op.utils.spark.RichVector.RichSparseVector
 import com.salesforce.op.utils.spark.{OpVectorColumnHistory, OpVectorMetadata}
 import enumeratum.{Enum, EnumEntry}
 import org.apache.spark.annotation.Experimental
@@ -130,16 +130,11 @@ class RecordInsightsLOCO[T <: Model[T]]
 
  private def computeDiff
  (
- i: Int,
- oldInd: Int,
  featureSparse: SparseVector,
  baseScore: Array[Double]
  ): Array[Double] = {
- val oldVal = featureSparse.update(i, oldInd, 0.0)
  val score = modelApply(labelDummy, featureSparse.toOPVector).score
- val diffs = baseScore.zip(score).map { case (b, s) => b - s }
- featureSparse.update(i, oldInd, oldVal)
- diffs
+ baseScore.zip(score).map { case (b, s) => b - s }
  }
 
  private def sumArrays(left: Array[Double], right: Array[Double]): Array[Double] = {
@@ -225,7 +220,9 @@ class RecordInsightsLOCO[T <: Model[T]]
  val zdif = Array.fill(baseScore.length)(0.0)
  featureVec match {
  case Left(sparse) => (0 until sparse.size, sparse.indices).zipped
- .map { case (i, oldInd) => (i, oldInd, computeDiff(i, oldInd, sparse, baseScore)) }
+ .map { case (i, oldInd) =>
+ (i, oldInd, computeDiff(sparse.copy.updated(i, oldInd, 0.0), baseScore))
+ }
  case Right(zeroeIndices) => (0 until zeroeIndices.length, zeroeIndices).zipped
  .map { case (i, oldInd) => (i + offset, oldInd, zdif) }
  }

features/src/main/scala/com/salesforce/op/utils/spark/RichVector.scala

@@ -134,20 +134,11 @@ object RichVector {
  }
 
  implicit class RichSparseVector(val v: SparseVector) extends AnyVal {
- def foreachNonZeroIndexedValue(f: (Int, Int, Double) => Unit): Unit = {
- (0 until v.indices.length)
- .withFilter(v.values(_) != 0.0)
- .foreach(i => f(i, v.indices(i), v.values(i)))
- }
-
- def update(index: Int, indexVal: Int, value: Double): Double = {
+ def updated(index: Int, indexVal: Int, value: Double): SparseVector = {
  require(v.indices(index) == indexVal,
  s"Invalid index: indices($index)==${v.indices(index)}, expected: $indexVal")
- val oldVal = v.values(index)
  v.values(index) = value
- oldVal
+ v
  }
-
- def toIndexedArray: Array[(Int, Double)] = v.indices.zip(v.values)
  }
 }