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From danielblazevski <...@git.apache.org>
Subject [GitHub] flink pull request: [FLINK-1745] Add exact k-nearest-neighbours al...
Date Wed, 09 Dec 2015 23:18:56 GMT
Github user danielblazevski commented on a diff in the pull request:

    https://github.com/apache/flink/pull/1220#discussion_r47168358
  
    --- Diff: flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/nn/QuadTree.scala
---
    @@ -0,0 +1,340 @@
    +/*
    + * 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.flink.ml.nn.util
    +
    +import org.apache.flink.ml.math.{Breeze, Vector}
    +import Breeze._
    +
    +import org.apache.flink.ml.metrics.distances.{SquaredEuclideanDistanceMetric,
    +EuclideanDistanceMetric, DistanceMetric}
    +
    +import scala.collection.mutable.ListBuffer
    +import scala.collection.mutable.PriorityQueue
    +
    +/**
    + * n-dimensional QuadTree data structure; partitions
    + * spatial data for faster queries (e.g. KNN query)
    + * The skeleton of the data structure was initially
    + * based off of the 2D Quadtree found here:
    + * http://www.cs.trinity.edu/~mlewis/CSCI1321-F11/Code/src/util/Quadtree.scala
    + *
    + * Many additional methods were added to the class both for
    + * efficient KNN queries and generalizing to n-dim.
    + *
    + * @param minVec vector of the corner of the bounding box with smallest coordinates
    + * @param maxVec vector of the corner of the bounding box with smallest coordinates
    + * @param distMetric metric, must be Euclidean or squareEuclidean
    + * @param maxPerBox threshold for number of points in each box before slitting a box
    + */
    +class QuadTree(minVec: Vector, maxVec: Vector, distMetric: DistanceMetric, maxPerBox:
Int){
    +
    --- End diff --
    
    In case later down the road, someone may want to define a quadtree for some other purpose
and not need minDist, the kNN query only needs to enforce Euclidean/SquaredEuclidean because
of the minDist function that defines the distance between a point and a box


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