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From mengxr <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-3218, SPARK-3219, SPARK-3261, SPARK-342...
Date Mon, 06 Oct 2014 21:50:01 GMT
Github user mengxr commented on a diff in the pull request:

    https://github.com/apache/spark/pull/2634#discussion_r18488352
  
    --- Diff: mllib/src/main/scala/org/apache/spark/mllib/clustering/metrics/EuclideanOps.scala
---
    @@ -0,0 +1,67 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.mllib.clustering.metrics
    +
    +import breeze.linalg.{DenseVector => BDV, SparseVector => BSV, Vector => BV}
    +import org.apache.spark.mllib.base.{Centroid, FPoint, PointOps, Infinity, Zero}
    +import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector}
    +
    +
    +/**
    + * Euclidean distance measure
    + *
    + * This is the slow implementation of the squared Euclidean distance function,
    + * shown here simply for clarity.
    + */
    +class EuclideanOps extends PointOps[FPoint, FPoint] with Serializable {
    +
    +  type C = FPoint
    +  type P = FPoint
    +
    +  val epsilon = 1e-4
    +
    +  def distance(p: P, c: C, upperBound: Double = Infinity): Double = {
    +    val d = p.inh.zip(c.inh).foldLeft(Zero) {
    +      case (d: Double, (a: Double, b: Double)) => d + (a - b) * (a - b)
    +    }
    +    if( d < Zero) Zero else d
    --- End diff --
    
    `if (d < Zero)` (space after `if` and no space after `(`)


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