How do adjM work?
John, Sam, Carl, Tory, or whoever -
There's no need to keep switching names. Pick one and stay with it.
We each had questions
I assume you are referring to the term "adjM," which could stand for "adjacency matrix." An adjacency matrix is a data structure used to represent a graph or a network. It provides a convenient way to store and manipulate the connections between nodes.
To understand how an adjacency matrix works, let me explain the process of creating one:
1. Determine the number of nodes in the graph: First, you need to know the number of nodes in the graph. Let's say you have N nodes.
2. Create an N x N matrix: An adjacency matrix is a square matrix with N rows and N columns, where each cell represents the connection between two nodes.
3. Initializing the matrix: Initially, set all the cells to 0 (or False) to indicate that there is no direct connection between any two nodes.
4. Creating connections: To represent the connections between nodes, you can update the matrix by setting the corresponding cell to 1 (or True) if there is an edge between the two nodes. For example, if node A is connected to node B, you would set the cell (A, B) and (B, A) to 1.
5. Using weights: In some cases, graphs may have weighted edges which represent the strength or cost of the connection. In such situations, instead of using 0s and 1s, you can assign the weights to the corresponding cells.
To access information from an adjacency matrix, you can simply refer to a specific cell (row, column) to check if there is a connection between two nodes. You can also iterate through the matrix to analyze the relationships between nodes or perform graph algorithms.
Note that adjacency matrices are most efficient for dense graphs (where most of the nodes are connected to each other) since they need N^2 space to store the connections. For sparse graphs (where very few connections exist), you may consider using an alternative data structure like an adjacency list.