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)
     }
   }