Suggestion for simple distance metric (and measure) design

distance.scala

import breeze.linalg.{Vector => BV, DenseVector => DBV}
import org.apache.spark.annotation.Experimental
import org.apache.spark.mllib.linalg.{Vector, DenseVector}

trait DistanceMeasure extends Function2[BV[Double], BV[Double], Double] with Serializable {
  // each measure/metric defines for itself:
  override def apply(v1: BV[Double], v2: BV[Double]): Double

  // a catch-all overloading of "()" for spark vectors
  // can also be overridden on a per-class basis, if it is advantageous
  def apply(v1: Vector, v2: Vector): Double = this(v1.toBreeze, v2.toBreeze)
}

trait DistanceMetric extends DistanceMeasure

class EuclideanDistance extends DistanceMetric {
  override def apply (v1: BV[Double], v2: BV[Double]): Double = {
    val d = v1 - v2
    Math.sqrt(d dot d)
  }
}

class WeightedEuclideanDistance(val weights: BV[Double]) extends DistanceMetric {
  override def apply (v1: BV[Double], v2: BV[Double]): Double = {
    val d = v1 - v2
    Math.sqrt(d dot (weights :* d))
  }
}

// a measure, not a metric
class CosineDistance extends DistanceMeasure {
  override def apply (v1: BV[Double], v2: BV[Double]): Double = {
    1.0 - ((v1 dot v2) / Math.sqrt((v1 dot v1) * (v2 dot v2)))
  }
}