Algorithm 闭包参数列表的上下文类型需要1个参数，但指定了2个

我正在尝试使该算法与swift 2.1配合使用：

虽然我在这一行中得到了错误：

  return map(Zip2Sequence(centroids, clusterSizes)) { Cluster(centroid: $0, size: $1) }

以下是完整的功能：

func kmeans<T : ClusteredType>(
        points: [T],
        k: Int,
        seed: UInt32,
        distance: ((T, T) -> Float),
        threshold: Float = 0.0001
    ) -> [Cluster<T>] {

    let n = points.count
    assert(k <= n, "k cannot be larger than the total number of points")

    var centroids = points.randomValues(seed, num: k)
    var memberships = [Int](count: n, repeatedValue: -1)
    var clusterSizes = [Int](count: k, repeatedValue: 0)

    var error: Float = 0
    var previousError: Float = 0

        repeat {
            error = 0
            var newCentroids = [T](count: k, repeatedValue: T.identity)
            var newClusterSizes = [Int](count: k, repeatedValue: 0)

            for i in 0..<n {
                let point = points[i]
                let clusterIndex = findNearestCluster(point, centroids: centroids, k: k, distance: distance)
                if memberships[i] != clusterIndex {
                    error += 1
                    memberships[i] = clusterIndex
                }
                newClusterSizes[clusterIndex]++
                newCentroids[clusterIndex] = newCentroids[clusterIndex] + point
            }
            for i in 0..<k {
                let size = newClusterSizes[i]
                if size > 0 {
                    centroids[i] = newCentroids[i] / size
                }
            }

            clusterSizes = newClusterSizes
            previousError = error
        } while abs(error - previousError) > threshold

        return map(Zip2Sequence(centroids, clusterSizes)) { Cluster(centroid: $0, size: $1) }
}

func-kmeans(
要点：[T]，
k:Int，
种子：UInt32，
距离：（（T，T）->浮动），
阈值：浮动=0.0001
)->[集群]{
设n=points.count
断言（k据我所知，您正试图实现以下目标：

return (0..<k).map { Cluster(centroid: centroids[$0], size: clusterSizes[$0]) }

return Zip2Sequence(centroids, clusterSizes).map { Cluster(centroid: $0.0, size: $0.1) }