当前课程知识点:计算几何 > 06. Point Location > J. Performance Of Trapezoidal Map > 06-J-10. Probability Of Enclosing Trapezoid Changed
当然
即便出现了刚才说的第二种情况
我们所需要花费的时间
也不至于会多出很多
它是可以度量和界定的
具体是多少呢
我们说具体的
也充其量不过是一个常数4
因为一个梯形
原来的那个梯形
至多会被分成四块
我们最多只需要进行常数的时间
就可以从中挑选出
继续应该往哪
继续深入下去
所以这是个好消息
当然相应的在search structure中
我们的查找也会向下深入若干层
你只要去翻看一下
我们此前关于构造梯形图算法中
所介绍的那三大类情况
就不能发现
在这种情况下search structure
尽管它的深度
会在这个局部有所增加
但是最坏的一种可能
充其量也不过只增加三层
也是个常数
当然我们所关心的是
最终平均而言
q所在的那个梯形
在search structure中有多深
而不难理解
我们最终这个search structure的高度
其实无非就是这样一系列
概率的总和
什么概率呢
也就是
在每一次插入一条新的线段以后
同样的这个相对固定的点q
它所属的那个梯形发生了变化
正如刚才我们说的
不发生变化
深度在这个位置上至少不会变
发生了变化
才会在这上有变化
那么我们刚才也看到了
这个变化的数量是3
是一个常数
所以最核心的
实际上就是这个概率的总和
为此我们不妨将这个probability
记作P_k
表示在第k条线段插入的过程中
引起这个q所属的梯形
发生变化的概率
那么我们只要能够估算出这个P_k
也自然就可以估算出
search structure的高度是多少了
-Before we start
--html
-Evaluation
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-Online Judge
--html
-Lecture notes
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-Discussion
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-A. History of This Course
--00-A. History of This Course
-B. What's Computational Geometry
--00-B. What's Computational Geometry
-B. What's Computational Geometry--作业
-C. How to Learn CG Better
--00-C. How to Learn CG Better
-C. How to Learn CG Better--作业
-D. Why English
-A. Convexity
-A. Convexity--作业
-B. Extreme Points
-B. Extreme Points--作业
-C. Extreme Edges
-C. Extreme Edges--作业
-D. Incremental Construction
--01-D-01. Decrease and Conquer
--01-D-02. In-Convex-Polygon Test
--01-D-03. Why Not Binary Search
-D. Incremental Construction--作业
-E. Jarvis March
--01-E-06. Lowest-Then-Leftmost
-E. Jarvis March--作业
-F. Lower Bound
--01-F-02. CAO Chong's Methodology
-F. Lower Bound--作业
-G. Graham Scan: Algorithm
-G. Graham Scan: Algorithm--作业
-H. Graham Scan: Example
-H. Graham Scan: Example--作业
-I. Graham Scan: Correctness
-I. Graham Scan: Correctness--作业
-J. Graham Scan: Analysis
-J. Graham Scan: Analysis--作业
-K. Divide-And-Conquer (1)
-K. Divide-And-Conquer (1)--作业
-L. Divide-And-Conquer (2)
--01-L-03. Topmost + Bottommost ?
--01-L-07. More Considerations
-L. Divide-And-Conquer (2)--作业
-M. Wrap-Up
-0. Introduction
-0. Introduction--作业
-A. Preliminary
-A. Preliminary--作业
-B. Interval Intersection Detection
-B. Interval Intersection Detection--作业
-C. Segment Intersection Reporting
-C. Segment Intersection Reporting--作业
-D. BO Algorithm: Strategy
--02-D-01. Proximity & Separability
--02-D-02. Comparability & Ordering
-D. BO Algorithm: Strategy--作业
-E. BO Algorithm: Implementation
--02-E-03. Events & Operations
-E. BO Algorithm: Implementation--作业
-F. BO Algorithm: Analysis
--02-F-04. Complexity of Event Queue
--02-F-05. Complexity of Status Structure
-F. BO Algorithm: Analysis--作业
-G. Convex Polygon Intersection Detection
--02-G-01. Problem Specification
--02-G-02. Monotone Partitioning
--02-G-04. Decrease-And-Conquer
-G. Convex Polygon Intersection Detection--作业
-H. Edge Chasing
--02-H-01. Eliminating Sickles
-H. Edge Chasing--作业
-I. Plane Sweeping
-I. Plane Sweeping--作业
-J. Halfplane Intersection Construction
-J. Halfplane Intersection Construction--作业
-0. Methodology
-0. Methodology--作业
-A. Art Gallery Problem
--03-A-02. Lower & Upper Bounds
--03-A-04. Approximation & Classification
-A. Art Gallery Problem--作业
-B. Art Gallery Theorem
--03-B-01. Necessity of floor(n/3)
--03-B-02. Sufficiency by Fan Decomposition
-B. Art Gallery Theorem--作业
-C. Fisk's Proof
--03-C-04. Pigeon-Hole Principle
-C. Fisk's Proof--作业
-D. Orthogonal Polygons
--03-D-01. Necessity of floor(n/4)
--03-D-02. Sufficiency by Convex Quadrilateralization
-D. Orthogonal Polygons--作业
-E. Triangulation
-E. Triangulation--作业
-F. Triangulating Monotone Polygons
--03-F-02. Monotonicity Testing
--03-F-04. Stack-Chain Consistency
-F. Triangulating Monotone Polygons--作业
-G. Monotone Decomposition
-G. Monotone Decomposition--作业
-I. Tetrahedralization
--03-I-01. Polyhedron Decomposition
--03-I-02. Schonhardt's Polyhedron
-I. Tetrahedralization--作业
-A. Introduction
--04-A-02. Dining Halls on Campus
--04-A-03. More Analogies & Applications
-A. Introduction--作业
-B. Terminologies
--04-B-02. Intersecting Halfspaces
--04-B-04. Planar Voronoi Diagram
-B. Terminologies--作业
-C. Properties
--04-C-03. Nearest = Concyclic
--04-C-04. Number of Nearest Sites = Degree
-C. Properties--作业
-D. Complexity
-D. Complexity--作业
-E. Representation
-E. Representation--作业
-F. DCEL
-F. DCEL--作业
-G. Hardness
--04-G-03. Voronoi Diagram In General Position
-G. Hardness--作业
-H. Sorted Sets
--04-H-01. Convex Hull Made Easier
--04-H-02. Convex Hull As A Combinatorial Structure
--04-H-03. Voronoi Diagram As A Geometric Structure
-H. Sorted Sets--作业
-I. VD_sorted
--04-I-06. Sorting Not Made Easier
-I. VD_sorted--作业
-J. Naive Construction
-J. Naive Construction--作业
-K. Incremental Construction
-K. Incremental Construction--作业
-L. Divide-And-Conquer
--04-L-09. Intersecting with Cells
-L. Divide-And-Conquer--作业
-M. Plane-Sweep
--04-M-09. Circle Event: What, When & Where
-M. Plane-Sweep--作业
-A. Point Set Triangulation
-A. Point Set Triangulation--作业
-B. Delaunay Triangulation
-B. Delaunay Triangulation--作业
-C. Properties
-C. Properties--作业
-D. Proximity Graph
--05-D-02. Relative Neighborhood Graph
-D. Proximity Graph--作业
-E. Euclidean Minimum Spanning Tree
-E. Euclidean Minimum Spanning Tree--作业
-F. Euclidean Traveling Salesman Problem
-G. Minimum Weighted Triangulation
-G. Minimum Weighted Triangulation--作业
-H. Construction
--05-H-03. Maximizing The Minimum Angle
--05-H-04. Evolution By Edge Flipping
-H. Construction--作业
-I. RIC With Example
-I. RIC With Example--作业
-J. Randomized Incremental Construction
--05-J-01. Recursive Implementation
--05-J-02. Iterative Implementation
-J. Randomized Incremental Construction--作业
-K. RIC Analysis
--05-K-04. Types Of Edge Change
--05-K-05. Number Of Edge Changes
--05-K-07. Number Of Rebucketings
--05-K-08. Probability For Rebucketing
--05-K-10. Further Consideration
-0. Online/Offline Algorithms
--06-0. Online/Offline Algorithms
-0. Online/Offline Algorithms--作业
-A. Introduction
--06-A-03. Assumptions For Clarity
--06-A-05. Performance Measurements
-A. Introduction--作业
-B. Slab Method
--06-B-02. Ordering Trapezoids
-B. Slab Method--作业
-C. Persistence
--06-C-01. Ephemeral Structure
--06-C-02. Persistent Structure
-C. Persistence--作业
-D. Path Copying
--06-D-03. Storage Optimization
-D. Path Copying--作业
-E. Node Copying
-E. Node Copying--作业
-F. Limited Node Copying
-G. Kirkpatrick Structure
--06-G-01. Optimal And Simpler
--06-G-06. The More The Better
--06-G-07. The Fewer The Better
--06-G-09. Existence Of Independent Subset
--06-G-10. Construction Of Independent Subset
-G. Kirkpatrick Structure--作业
-H. Trapezoidal Map
--06-H-03. Properties & Complexity
--06-H-04. Search Structure: Example
--06-H-05. Search Structure: Nodes
--06-H-06. Search Structure: Performance
-H. Trapezoidal Map--作业
-I. Constructing Trapezoidal Map
--06-I-04. Case 1: Two Endpoints
--06-I-05. Case 2: One Endpoint
--06-I-06. Case 3: No Endpoints
-J. Performance Of Trapezoidal Map
--06-J-03. Number Of Ray Trimmed
--06-J-04. Number Of Trapezoidals Created (1)
--06-J-05. Number Of Trapezoidals Created (2)
--06-J-06. Time For Point Location
--06-J-07. Size Of Search Structure
--06-J-08. Fixed Query Point + Randomly Created Maps
--06-J-10. Probability Of Enclosing Trapezoid Changed
-A. Range Query
--07-A-01. 1-Dimensional Range Query
-A. Range Query--作业
-B. BBST
--07-B-02. Lowest Common Ancestor
-B. BBST--作业
-C. kd-Tree: Structure
-C. kd-Tree: Structure--作业
-D. kd-Tree: Algorithm
-D. kd-Tree: Algorithm--作业
-E. kd-Tree: Performance
--07-E-01. Preprocessing Time + Storage
-E. kd-Tree: Performance--作业
-F. Range Tree: Structure
--07-F-03. x-Query * y-Queries
-F. Range Tree: Structure--作业
-G. Range Tree: Query
-G. Range Tree: Query--作业
-H. Range Tree: Performance
-H. Range Tree: Performance--作业
-I. Range Tree: Optimization
--07-I-04. Fractional Cascading
-A. Orthogonal Windowing Query
-A. Orthogonal Windowing Query--作业
-B. Stabbing Query
-C. Interval Tree: Construction
-C. Interval Tree: Construction--作业
-D. Interval Tree: Query
-D. Interval Tree: Query--作业
-E. Stabbing With A Segment
--08-E-03. Query Algorithm (1)
--08-E-04. Query Algorithm (2)
-F. Grounded Range Query
--08-F-03. 1D-GRQ Using Range Tree
--08-F-04. 1D-GRQ By Linear Scan
-G. 1D-GRQ Using Heap
-G. 1D-GRQ Using Heap--作业
-H. Priority Search Tree
--08-H-03. Sibling Partitioning
-H. Priority Search Tree--作业
-I. 2D-GRQ Using PST
-I. 2D-GRQ Using PST--作业
-J. Segment Tree
--08-J-01. General Windowing Query
--08-J-02. Elementary Interval
--08-J-06. Solving Stabbing Query
--08-J-11. Constructing A Segment Tree
--08-J-12. Inserting A Segment (1)
--08-J-13. Inserting A Segment (2)
--08-J-14. Inserting A Segment (3)
-K. Vertical Segment Stabbing Query