Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/3462#discussion_r20921781
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
---
@@ -261,6 +261,57 @@ object Vectors {
sys.error("Unsupported Breeze vector type: " + v.getClass.getName)
}
}
+
+ /**
+ * Returns the p-norm of this vector.
+ * @param vector input vector.
+ * @param p norm.
+ * @return norm in L^p^ space.
+ */
+ private[spark] def norm(vector: Vector, p: Double): Double = {
+ require(p >= 1.0)
+ val values = vector match {
+ case dv: DenseVector => dv.values
+ case sv: SparseVector => sv.values
+ case v => throw new IllegalArgumentException("Do not support vector
type " + v.getClass)
+ }
+ val size = values.size
+
+ if (p == 1) {
+ var sum = 0.0
+ var i = 0
+ while (i < size) {
+ sum += math.abs(values(i))
+ i += 1
+ }
+ sum
+ } else if (p == 2) {
+ var sum = 0.0
+ var i = 0
+ while (i < size) {
+ sum += values(i) * values(i)
--- End diff --
Since this is a common case and tight loop, avoid the duplicated value
lookup?
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