spark 2.0 Vector toBreeze

  def toBreeze( _v : Vector ) : BZV[Double] = {
    _v match {
      case x : org.apache.spark.mllib.linalg.DenseVector => new BDV(_v.toArray)
      case x : org.apache.spark.mllib.linalg.SparseVector => {
        val sparseVector = _v.toSparse
        new BSV(sparseVector.indices, sparseVector.values, sparseVector.size)
      }
      case _ => {new BDV(Array[Double]())}
    }
  }

  def fromBreeze(breezeVector: BZV[Double]): Vector = {
    breezeVector match {
      case v: BDV[Double] =>
        if (v.offset == 0 && v.stride == 1 && v.length == v.data.length) {
          new org.apache.spark.mlllib.linalg.DenseVector(v.data)
        } else {
          new org.apache.spark.mlllib.linalg.DenseVector(v.toArray)  // Can't use underlying array directly, so make a new one
        }
      case v: BSV[Double] =>
        if (v.index.length == v.used) {
          new org.apache.spark.mlllib.linalg.SparseVector(v.length, v.index, v.data)
        } else {
          new org.apache.spark.mlllib.linalg.SparseVector(v.length, v.index.slice(0, v.used), v.data.slice(0, v.used))
        }
      case v: BZV[_] =>
        sys.error("Unsupported Breeze vector type: " + v.getClass.getName)
    }
  }