数据结构英文课件GRAPHS.ppt

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Python英文PPT课件:31-Graphs3

Python英文PPT课件:31-Graphs3
object AbstractCollection
AbstractGraph
MatrixDirectedGraph MatrixUndirectedGraph
LinkedDirectedGraph LinkedUndirectedGraph
Fundamentals of Python: Data Structures
• Directed
– Adjacency matrix – Adjacency list
• Undirected
– Adjacency matrix – Adjacency list
Fundamentals of Python: Data Structures
3
Possible Organization: Directed Graphs
5
Related Auxiliary Classes
object
Vertex
Edge
MatrixVertex
LinkedVertex MatrixEdge
LinkedEdge
Fundamentals of Python: Data Structures
6
The Graph Interface: Basic Methods
7
The Graph Interface: Iterators
g.edges() g.vertices() g.incidentEdges(vertexLabel) g.neighboringVertices(vertexLabel)
# Adjacent vertices
Fundamentals of Python: Data Structures
g.addEdge("A", "B", 2.5) g.addEdge("B", "C", 2.5) g.addEdge("C", "B", 2.5) print("Expect same vertices and edges AB BC CB all with weight 2.5: \n" + str(g))

图形结构(Graphs)汇总

图形结构(Graphs)汇总
G3
圖形的一些專有名詞
外分支度(out-degree):頂 點V的外分支度是以V為起 點的邊數。 如: G3中頂點2的內分 支度為2 而外分支度為 1,分支度為3 而無方向圖形則無內外 之分,如: G2中頂點2 的分支度為3,頂點5的 分支度為1
G3
圖形資料結構表示法

圖形的資料結構表示法常用的有下列二種: 相鄰矩陣(adjacent matrix) 相鄰串列(adjacent list)
V4
V6 V9 V10
V7
V5 V3
圖形追蹤

彈出V1,由於V1已被輸出,故捨棄不用,接著 再彈出V4,將V4的相鄰頂點V2及V8放入堆疊。
V1 V2 V3 V5 V8
V1
V2 V8 V5 V3
V4
V4
V5
V6 V9 V10
V7
V3
輸出:V1 V2 V4
圖形追蹤

彈出V2,由於V2已被輸出過,故捨棄不用,接 著再彈出V8,再將V8的相鄰頂點V4、V5及V10放 入堆疊。 V1
圖形的一些專有名詞

連通單元(connected component):或稱單元 (component)是指該圖形中最大的連通子圖 (maximum connected subgraph)如圖G5有兩 個單元g1和g2。
1 5
3
4
2
6
8
G5
7
圖形的一些專有名詞

緊密連通(strongly connected):在一有 方向圖形中如果V(G) 中的每一對不同頂點Vi, Vj 各有一條從Vi到Vj及 從Vj到Vi的有方向路徑 者稱之。
V3 V9 V9 V7 V10 V5 V3

数据结构PPT课件精品 图2(ppt文档)

数据结构PPT课件精品 图2(ppt文档)

B 0 03 5 8
5 8 4 1 30∞4
C 2D
2 5∞ 0 2 3 8 4 20
⑤ 删除顶点Vertex
算法思想:不仅要从顶点链表中删除该顶点, 还需要删除该顶点所发出的边以及 所有的入边,即在邻接矩阵中删除 相应的行和列。
template<class T> Void Graph<T>::DeleteVertex(const T& vertex) {
● Graph类的实现 ① 构造函数
template<class T> Graph<T> :: Graph( const int sz = Default )
graphsize( 0 ), MaxGraphSize( sz ), NumEdge( 0 ) { int n , e , weight ; T name , from , to ;
for (row=pos+1;row<=graphsize; row++) for(col=pos+1; col<= graphsize; col++) edge[row-1][col-1]= edge[row][col];
}
有向图的逆邻接表
V0
V1
0 V0
V2 1 V1
2 V2 ∧
V4
V3
3 V3
int edge[ MaxGraphSize ][ MaxGraphSize ] ; //邻接矩阵
int graphsize ; //当前顶点数
//当前边数
int CurrentEdges ;
//检查顶点vertex是否已在顶点表L中 int FindVertex( SeqList<T> & L ,

数据结构 图

数据结构 图
2)依次访问 vi 的所有未被访问的邻接点; 3)从这些邻接点出发,访问它们的所有未被访问的 邻接点; 依此类推,直到图中所有的顶点的邻接 点都被访问。 例 求图G 的以V0起点的的广度优先序列 V0,V1,V2,V3,V4,V5,V6,V7 V V
0 0
由于没有规定 访问邻接点的顺序, 广度优先序列不唯一。
则图的所有顶点的度数之和 = 2*e
V2
V3
(每条边对图的所有顶点的度数之和 “贡献” 2度)
3 路径、回路(环)
无向图G1=(V1,E1)中的顶点序列v1,v2,… ,vk,若 (vi,vi+1)E1 ( i=1,2,…k-1), v =v1, u =vk, 则称该序 列是从顶点v到顶点u的路径;若v=u,则称该序 列为回路;在G1中,v0,v1,v2,v3 是v0到v3的路径; v0,v1,v2,v3 , v0是回路; 有向图G2=(V2,E2)中的顶点序列v1,v2,… ,vk, <vi,vi+1>E2 (i=1,2,…k-1),若v =v1, u =vk,则称该 序列是从顶点v到顶点u的路径;若v=u,则称该序 V0 V1 V1 列为回路;在G2中, V0 V2 v0, v2, v3是v0到v3的路径 v0,v2,v3,v0是回路; V3 V4 V2 V3 无向图G1 有向图G2
V2
V3
非 强 连 通 图
5 子图
设有两个图G=(V,E)、G1= (V1,E1), 若V1 V,E1 E,E1关联的顶点都在V1中, 则称 G1是G的子图;

V0 V2 V3 (a) V4 V3 (b) V1
下列 (b)、(c) 是 (a) 的子图
V0 V2 V4 V3 (c) V1

第06章图Graph-PPT精品文档

第06章图Graph-PPT精品文档

Example:

SFO HNL
ORD LGA
PVD
LAX
DFW
Graphs
MIA
3
Edge Types
Directed edge


ordered pair of vertices (u,v) first vertex u is the origin second vertex v is the destination e.g., a flight
a U c
V
b
Simple path

d P2
W f
P1 X h Z
e g Y
Examples

Graphs
7
Terminology (cont.)
Cycle


circular sequence of alternating vertices and edges each edge is preceded and followed by its endpoints
Байду номын сангаас
Printed circuit board Integrated circuit
Transportation networks


Highway network Flight network


Computer networks

U and V are the endpoints of a a, d, and b are incident on V U and V are adjacent X has degree 5 h and i are parallel edges j is a self-loop

离散数学课件(英文版)----Graph

离散数学课件(英文版)----Graph
A D C A D
C
B
B
Graph and Diagram
Graph G is a triple: G =〈VG, EG, 〉
VG and EG are sets,satisgying VGEG=φ, :EG {{vi, vj}| vi, vj∈VG} Note: {vi, vj}={vj, vi} A graph can be represented conveniently by some diagram: : each element of VG as a dot, the vertex, and each element of EG as a line segment, the edge, between vertices. So, VG is called the set of vertices, and EG, the set of edges.
i i =1
The number of vertices with odd degree must be even.
Complete Graph
A graph is a complete graph if and only if any two of its vertices are adjacent.
Subgraph
Let G=<V,E>, G’=<V’,E’>, if V’V, E’E, then G’is called a subgraph of G. If V’V, or E’E, then G’ is a proper subgraph. If V’=V, then G’ is a spanning subgraph.
Determination of Euler Graph

Chapter11 Graphs

Chapter11 Graphs

Searches
Depth-First Search(深度优先查找) It uses a stack to remember where it should go when it reaches a dead end (死胡同). 1.Pick a starting point (A)
(1)visit this vertex, (2)push it onto a stack (3)mark it
Searches
2.Go to any vertex adjacent to A that hasn’t yet been visited. Repeat 1(1)~(3)
Searches
RULE 1 If possible, visit an adjacent unvisited vertex, mark it, and push it on the stack. RULE 2 If you can’t follow Rule 1, then, if possible, pop a vertex off the stack. RULE 3 If you can’t follow Rule 1 or Rule 2, you’re done.
A B C D
class Vertex { public char label; // label (e.g. ‘A’) public boolean wasVisited; public Vertex(char lab) // constructor { label = lab; wasVisited = false;
D 1 1 0 0 0
F 0 1 0 0 0 0
B
C D F
The Graph Class

第八章 图(Graph)PPT课件

第八章 图(Graph)PPT课件
Graph->Arcs[v][w] = 0; }
15
2、邻接表 (Adjacency List)表示法
实际上是一种顺序存储与链式存储相结合的方法。顺序存储 部分用来存储图中顶点的信息,链式部分用来保存图中边 (弧)的信息。
一个一维数组,每个数据元素包含以下信息:
Vertex FirstArc
邻接单链表的每个结点(边结点)的结构如下 AdjVertex Weight NextArc
16
# define MAXNODE <图中结点的最大个数>
typedef struct arc {
int AdjVertex; int Weight; struct arc * NextArc; }arctype; // 邻接链表结点结构
typedef struct {
elemtype Vertext; arctype * FirstArc; }vertextype; // 顺序表结构
在无向图中, 统计第 i 行 (列) 1 的个数可得顶点i 的度。
12
网络的邻接矩阵 W (i,j), 如i果 !j且 <i,jE或 (i,j)E
A.Ed[i]gj[]e= , 否但 则i是 !,=j 0, 对角 i=线 j=
13
用邻接矩阵表示的图的类型的定义
#define MAXNODE 100
✓权 某些图的边具有与它相关的数, 称之为权。这 种带权图叫做网络。
8
7
10 2
5 9
1
12
63
8
15
76
6
3
4
16
7
施工进度图
60
A
B 40 80 C
30

第06章图Graph讲解学习

第06章图Graph讲解学习

9
Subgraphs
A subgraph S of a graph G is a graph such that
The vertices of S are a subset of the vertices of G
The edges of S are a subset of the edges of G
Edge List
Adjacency List
Adjacency Matrix
n+m
n+m
n2
m
deg(v)
n
m min(deg(v), deg(w))
1
1
1
n2
1
1
1
m
deg(v)
n2
1
1
1
Graphs
19
6.3 Graph Traversal
Graphs
20
6.3.1 Depth-First Search
Ud
X
Z
C2
h
c
e C1
W
g
fY
Graphs
8
Properties
Property 1
Sv deg(v) = 2m
Proof: each edge is counted twice
Property 2
In an undirected graph with no self-loops and no multiple edges m n (n - 1)/2
Depth-first search (DFS) is a general technique for traversing a graph
A spanning subgraph of G is a subgraph that contains all the vertices of G

graphs_ppt

graphs_ppt
ous data
useful for showing trends over time
What else must a graph have?
Teachers’ Favorite Singers
T - Title
What else must a graph have?
Teachers’ Favorite Singers
T - Title A - Axis
Y Axis = Dependent Variable X Axis = Independent Variable
Why graph?
After conducting an experiment, a graph can be used to visually represent data. Graphs allow a quick view of the data trends, if those exist Data trends are patterns that can be seen in the data Data trends can be used to predict what may happen if the experiment were to continue Data trends can also be used to explain the data and draw accurate conclusions
What else must a graph have?
Teachers’ Favorite Singers
The amount of space between one number and the next or one type of data and the next on the graph.

数据结构Chapter7 Graph

数据结构Chapter7 Graph

Figure7.10 Spanning Tree
A C D E D B A C E B
(a)Unirected graph
(b)Spanning tree
Graph Real-life Example
• • • • An airport system Highway system Traffic flow Communication system
Basic Operations on Graph
• • • • • • • CreateGraph(G) DestroyGraph(G) GetVex(G, v) PutVex(G, v, value) InsertVex(G, v) DeleteVex(G, v) InsertArc(G, v, w)
Graph
• If a directed graph is not strongly connected, but the underlying graph(without direction to the arcs) is connected, then the graph is said to be weakly connected. • A complete graph is a graph in which there is an egde between every pair of vertices.
Graph
• A cycle in a directed graph is a path of length at least 1 such that w1=wN; this cycle is simple if the path is simple. • For undirected graphs, we require that the edges be distinct. The logic of these requirements is that the path u,v,u is an undirected graph should not be considered a cycle, because (u,v) and (v,u) are the same edges.

第八章图GraphsTheeighthchapterGraphs-PPT精选

第八章图GraphsTheeighthchapterGraphs-PPT精选

mark ivex jverx ilink jlink
typedef emnu {unvisited,visited} Visited; typedef struct EBox{
Visited mark; //访问标记 int ivex,jvex;//该边依附的两个顶点的位置 struct EBox *ilink,*jlink;//分别指向依附这 两个顶点的下一条边 InfoType *info; //该边信息指针 }EBox;
其中 V = { x | x 某个数据对象} 是顶点的有穷非 空集合;
E = {<x, y> | x, y V } 是顶点之间关系的有穷集合,也叫做边(edge)的集合。
v1 v2 v3 v4
v1 v2 v3
v4 v5
(a) G1=(V1,E1)
(b) G2 = (V2, E2)
• 有向图G1 V1={v1,v2,v3,v4}, E1={<v1,v3>,<v1,v2>,<v3,v4>,<v4,v1>}
Typedef struct { //邻接表结构 AdjList vertices; int vexnum,arcnum; //图的当前顶点数和弧数
}ALGraph;
邻接表的特点
• 顶点vi的度恰为第i个链表中的结点数; • 在有向图中,第i个链表(出边表)中的结点个数是
顶点的出度;
•求入度必须遍历整个邻接表: 在所有链表中其 邻接点域的值为i的结点的个数是顶点vi的入度。 •为了求入度的便利, 可以建立逆邻接表, 即链表 为入边表;
则称顶点序列 ( vi vp1 vp2 ... vpm vj )
为从顶点vi 到顶点 vj 的路径。

数据结构和算法分析第6讲 图

数据结构和算法分析第6讲 图

若有<v, w>VR,必 由顶点集和边集构
有<w, v>VR,则称 成的图称作无向图
(v,w) 为顶点v和顶 点w之间存在一条边
BC
例如: G2=(V2,{VR2 }) A
D
V2={A, B, C, D, E, F}
F
E
VR2={<A,B>, <A,E>,
<B,E>, <C,D>, <D,F>, <B,F>, <C,F> }
2
E D

4E
0
有向图的十字链表存储表示
弧的结点结构
弧尾顶点位置 弧头顶点位置
弧的相关信息
指向下一个 有相同弧头 的结点
指向下一个 有相同弧尾 的结点
typedef struct ArcBox { // 弧的结构表示
int tailvex, headvex; InfoType *info;
struct ArcBox *hlink, *tlink;
for(w=FirstAdjVex(g, v);w>=0; w=NextAdjVex(g,v,w)) {
if ( !visited[w] ){ cout << GetVex(g, w); EnQueue ( q, w); visited[w ] = true;
} } };
最小代价生成树 (minimum cost spanning tree)
结构的建立和销毁
CreatGraph(&G, V, VR): //按定义(V, VR) 构造图
DestroyGraph(&G): //销毁图
对顶点的访问操作

数据结构Chap8 graph

数据结构Chap8 graph
need two vertices.
To identify a arc
need both source and destination vertices.
Find Vertex
Retrieve vertex traverses a graph looking for a specified vertex.
8-4-1 Adjacency Matrix 8-4-2 Adjacency List
8-5 graph algorithms 8-6 Graph ADT 8-7 networks
8-7-1 minimum spanning tree 8-7-2 shortest path algorithm
8-1 terminology
If the vertex is found, its data are returned. If it is not found, an error is indicated.
Data Structures and Algorithms
Chapter 8: Graphs
College of Electronic and Information Engineering Chongqing University of Science and Technology
Instructor: Xiong Qian
More Graph Concepts
Two vertices are adjacent if an edge directly connects them
A path is a sequence of adjacent vertices A cycle is a path that starts and ends with
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8. A cycle is a path containing at least three vertices such that the last vertex on the path is adjacent to the first.
9. A graph is called connected if there is a path from any vertex to any other vertex.
13.The valence of a vertex is the number of edges on which it lies, hence also the number of vertices adjes of Graphs
Various kinds of undirected graphs
Chapter 12 GRAPHS
1. Mathematical Background 2. Computer Representation 3. Graph Traversal 4. Topological Sorting 5. A Greedy Algorithm: Shortest Paths 6. Minimal Spanning Trees 7. Graphs as Data Structures
6. Two vertices in an undirected graph are called adjacent if there is an edge from the first to the second.
7. A path is a sequence of distinct vertices, each adjacent to the next.
10. A free tree is defined as a connected undirected graph with no cycles.
11. In a directed graph a path or a cycle means always moving in the direction indicated by the arrows. Such a path (cycle) is called a directed path (cycle).
directed graph
Set as a bit string: pg.573
template <int max_set> struct Set { bool is_element[max_set]; };
number of vertices at most max_size
Digraph as a bit-string set:
template <int max_size> class Digraph { int count;
Set<max_size> neighbors[max_size]; };
Adjacency matrix
Digraph as an adjacency table: pg.574
template <int max_size> class Digraph { int count;
12.A directed graph is called strongly connected if there is a directed path from any vertex to any other vertex. If we suppress the direction of the edges and the resulting undirected graph is connected, we call the directed graph weakly connected.
Examples of directed graphs
12.2 Computer Representation
Set Implementations of Digraphs pg.573
Definition A digraph G consists of a set V , called the vertices of G, and, for all vV, a subset Av of V, called the set of vertices adjacent to v.
2. The pairs in E are called the edges of G. 3. If e = (v,w) is an edge with vertices v and w, then v
and w are said to lie on e, and e is said to be incident with v and w. 4. If the pairs are unordered, G is called an undirected graph. 5. If the pairs are ordered, G is called a directed graph. The term directed graph is often shortened to digraph, and the unqualified term graph usually means undirected graph.
12.1 Mathematical Background
Definitions and Examples
依关附联于
1. A graph G consists of a set V , whose members are called the vertices of G, together with a set E of pairs of distinct vertices from V .
bool adjacency[max_size][max_size]; };
List Implementation of Digraphs
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