This is the 19th day of my participation in the Genwen Challenge
figure
The concept of the figure
Graph G is composed of vertex set V and edge set E, denoted as G=(V,E), where V(G) represents the finite non-empty set of vertices in graph G; E(G) represents the set of relations (edges) between vertices in graph G if V={v1,v2,v3… ,vnv_1,v_2,v_3… ,v_nv1,v2,v3… ,.vn}, use | V | for the vertices of a graph G number, also known as the order of graph G, E = {(u, V) | u ∈ V, V ∈ V \ in V, V/V ∈ V, in V ∈ V}, expressed in | E | article edges in the graph G
There are no empty graphs, i.e. graphs must have vertices
- Directed graph
- Undirected graph
- A simple figure
- There are no duplicate edges
- There are no edges from vertices to themselves
- Multigraph: As opposed to simple graph
- Complete graph: In an undirected graph, if there are edges between any two vertices, the graph is called an undirected perfect graph; an undirected perfect graph with n vertices has N (n-1) edges; in a directed graph, if there are two arcs between any two vertices with opposite directions, the graph is called a directed perfect graph. A directed perfect graph with n vertices has n(n-1) directed edges. In FIG. 5.1, G2G_2G2 is an undirected perfect graph, while G3G_3G3 is a directed perfect graph
- Subgraph: given two graphs G=(V,E) and G ‘=(V ‘,E’), G’ is said to be a subgraph of G if V’ is a subset of V and E’ is a subset of E. If G and G ‘have the same number of vertices, G’ is called a generated subgraph
- Connected, connected graphs, and connected components: The maximally connected subgraph of an undirected graph is called a connected component
- Strongly connected graph, strongly connected component: connected from vertex V to vertex W is strongly connected
- 3. A spanning tree or forest:
- The spanning tree of a connected graph is a minimal connected subgraph containing all the vertices in the graph
- In an unconnected graph, the spanning tree of connected components constitutes the spanning forest of the unconnected graph
- The degree, degree, or degree of a vertex:
- Degree of vertices in a graph: the number of edges of this vertex
- Entry: The number of directed edges terminating at vertex V,
- The sum of the intakes equals the sum of the outtakes, and equals the number of edges
- Edge weights and nets: Each edge has a number. A weighted graph is called a net
- Path, path length, loop: Path — a sequence of paths from vertex VP to vertex vq a sequence of paths from vertex Vq v_p,v_1,v_2, v_qVP to vertex vq vp,v1,v2,vq, the number of paths above is called path length, A path whose last vertex is the same as the first vertex is called a loop or ring. If a graph has n vertices and more than n-1 edges, the graph must have a ring
- Simple path, simple loop: a path with no repetition is called a simple path, and a path with no repetition except for the first vertex is called a simple loop
- Distance: the shortest path length from I to V
- A directed graph with a vertex of zero entry and other non-zero vertices is called a directed tree
How the graph is stored
Adjacency matrix < order >
A one-dimensional array stores information about vertices in the graph, and a two-dimensional array stores information about edges in the graph, which is called an adjacency matrix
The characteristics of
- The adjacency matrix of an undirected graph must be symmetric, so only half of it can be saved
- You can’t tell directly how many edges there are
- Dense graph fit
- The element A “[I][j] of A” is equal to the number of paths of length n from vertex I to vertex j
Adjacency list < links >
The characteristics of
- Thin figure
- If for undirected graph G, the required storage space is O (| V | | | E + 2); If G is have to plan for the O (+ | E | | V |)
- There is no direct way to see if there is an edge between two nodes
- It’s not easy to find the degree
- Adjacency list means not unique