B.S.D
The project implements a Weighted and directed graph model. The graph contains a data structure of a dictionary in a dictionary: the keys in the external dict are sources nodes keys, Every value is a pair (tuple) of (dest: weight), of an edge.
This project's weighted directed graph functions include:
- save_to_json- Saving the graph into a file of json
- load()- Loading a graph from a file
- shortestPath()- Find the lighted (the minimal weight of edges) path between two nodes using Dijkstra's algorithm, implemented by a queue
- shortestPathDist()- Returning the shortest path's between two nodes weight
- add(node_data node)- Adding nodes to a graph
- remove(node_data node)- Removing nodes from a graph
- AddEdge(node_data src, node_data dest)- #tochange- Adding neighbors to nodes in the graph- meaning creating an edge between two nodes, starting from the src node to the dest node
- RemoveEdge(node_data src, node_data dest)- Removing neighbors to nodes in the graph- meaning creating an edge between two nodes, starting from the src node to the dest node
- Receiving the neighbors of a particular junction
- setInfo()- Adding information to the nodes themselves, in two information values ("variables") for each node
- connected componnent(x) - returns the SCC of the node x
- connected_componnents() - returns al the SCC componnets in the graph
- all_out_edges_of_node(x) - returns all the dests of the node x
- all_in_edges_of_node(x) - returns all the srcs of the node x
- copy()- Deep copy of a graph
- load_from_json()- Loads a graph from a json file (within a specific structure. id defined in "How to use?".)
Tests of this graph include:
