So learning map this data structure and the way we learn is the same as before, we have to learn it from three aspects. The first is its logical structure, as well as some related concepts. Then it is storage structure as well as its operation. So then we look at the main points of this chapter to learn. First we will explain the logical structure of it and some related basic concepts. Then we will explain the storage structure diagram. FIG storage structure, there are four, namely, the adjacency matrix, the adjacency list method, the adjacent multi-table and orthogonal list. Then the first two representations are directed to storing and sequentially stored in the chain, is an extension of the latter two methods, in that they are directed against and non-directed graph. After this we will explain in detail. Then we'll talk about the graph traversal operation, there are two methods for traversing its main map speaking, the first one is the breadth-first traversal, the second is depth-first traversal. We will explain the details of its traversal and its algorithm. Finally, we have to explain some important applications related graphs. In PubMed, the most important applications there are four, namely, minimum spanning tree, shortest path, topological sorting and critical path. Well, this is the main points of this chapter to explain.
So this first lesson we first learn the basic concepts of drawing.
What is the view of it? Before we learned of this linear table linear structure it is one to one relationship, the last chapter we explain the relationship of one to many, it is a non-linear structure tree. Figure what to do with it? In the first chapter we learned, drawing many to many relationship.
That is, each node can have a number of nodes connected to it.
In the book is a diagram of how to define it? The book is well-defined. FIG set G by the vertex V and edges E composition, referred to as G = (V, E). We use this tuple represents a set of vertices and a set of edges G. FIG. It then speaks wherein V (G) represented by G in FIG finite non-empty set of vertices, E (G) shows a relationship between a set of vertices of graph G, it is what we call the set of edges.
Then we look at the following example, if it is a diagram which is G, represented by such tuple. So what set of vertices of the graph represent it? We use V braces circled all the vertices. In this FIG. Among then, a total of five vertices, namely, A, B, C, D, E, shows a set of vertices we use this method of FIG.
Then we look at is how to represent the set of edges. Edge set with a brace still circled all sides. Then each side is how to represent it? We use a small parenthesis to indicate a side, there are two letters in parentheses them, these two letters represent the two endpoints of the article edges. So why use a small parenthesis here to do? Then we will have a detailed explanation. OK, so we represent the set of edges. So A, B this edge, we use the parentheses A, B so expressed. This is the edge set representation.
Next we look, then there is a very important point is non-empty finite set of defining them, Why here finite non-empty set important?
Because it shows the figure is not empty. Cast your mind back, before we explained before, linear table may be empty, the tree may be empty, but here map must not be empty, this is no empty graph representation. Well, this is the definition which we should pay attention to one point.
Next we look good we use the absolute value symbol