Random Walk Based on Neighbor Degrees in Graph

This function performs a random walk on a graph G starting from the start_node for num_steps. At each step, the function chooses the next node based on the degree of the neighbors of the current node.

Technology Stack : NetworkX for graph operations, set for visited nodes, list for path and neighbors, lambda function for degree-based selection

Code Type : The type of code

Code Difficulty :

                
                    
def random_walk_degree(G, start_node, num_steps):
    """
    Perform a random walk on a graph G starting at start_node for num_steps.
    The walk will follow the degree of each node at each step.
    """
    import networkx as nx

    current_node = start_node
    visited = set()
    path = []

    for _ in range(num_steps):
        visited.add(current_node)
        path.append(current_node)

        # Get the neighbors of the current node
        neighbors = list(G.neighbors(current_node))

        # If there are no neighbors, break the loop
        if not neighbors:
            break

        # Choose the next node based on the degree of the neighbors
        next_node = max(neighbors, key=lambda node: G.degree(node))

        # Move to the next node
        current_node = next_node

    return path