December 2016
Intermediate to advanced
440 pages
9h 44m
Japanese
Content preview from アルゴリズムクイックリファレンス 第2版
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354
■
10
章 空間木構造
10.8.2
文脈
R
木
は、地理学的構造や、長方形や多角形といったより抽象的な
n
次元データを
含む多次元情報をインデックスできるように設計されている。この構造は、情報が
あまりに大きすぎてメインメモリに収まらないときにも優秀な実行時性能を出す数
少ない構造の
1
つである。伝統的なインデックス技法は本質的に
1
次元なので、
R
木
構造はこれらの領域によく適している。
R
木
の演算は挿入、削除と
2
種類のクエリからなる。
R
木
によって特定の長方形
領域を探したり、クエリ長方形に交差する長方形領域の集まりを決定できる。
10.8.3
解
次の
Python
実装では、任意の識別子を各長方形に付随させている。これを使っ
てデータベースから実際の空間オブジェクトを取り出すことになる。まず
R
木
の
基本要素の
RNode
から始める。各
RNode
は、境界領域と任意の識別子を保持する。
RNode
は、
node.level
が
0
なら葉である。
RNode
には、
node.count
個の子があって、
それらが
node.children
リストに格納されている。子の
RNode
が追加されると、親
の
node.region
の境界ボックスを調整して、新しく追加された子どもを含むように
しなければならない。
例
10-8
R
木の
RNode
実装
class RNode:
#
識別子を生成するための単調増加カウンタ
counter = 0
def __init__(self, M, rectangle = None, ident = None, ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.