AlgoDatSoSe24/SoSe24/lec06_graph/graph.py

from collections import deque
from typing import List
import re
from enum import Enum

class NodeColor(Enum):
    """Enumeration for node colors in a graph traversal."""
    WHITE = 1       # WHITE: not visited
    GRAY = 2        # GRAY: visited but not all neighbors visited
    BLACK = 3       # BLACK: visited and all neighbors visited



class Vertex:
    """A vertex in a graph."""
    def __init__(self, value):
        self.value = value

    def __repr__(self):
        return str(self.value)

class Graph:
    """A graph."""
    def insert_vertex(self, name: str):
        raise NotImplementedError("Please implement this method in subclass")

    def connect(self, name1: str, name2: str, weight: float = 1):
        raise NotImplementedError("Please implement this method in subclass")

    def all_vertices(self) -> List[Vertex]:
        raise NotImplementedError("Please implement this method in subclass")

    def get_vertex(self, name: str) -> Vertex:
        raise NotImplementedError("Please implement this method in subclass")

    def get_adjacent_vertices(self, name: str) -> List[Vertex]:
        raise NotImplementedError("Please implement this method in subclass")

    def get_adjacent_vertices_with_weight(self, name: str) -> List[tuple[Vertex, float]]:
        raise NotImplementedError("Please implement this method in subclass")


    def bfs(self, start_name: str):
        """
        Perform a breadth-first search starting at the given vertex.
        :param start_name: the name of the vertex to start at
        :return: a tuple of two dictionaries, the first mapping vertices to distances from the start vertex,
                 the second mapping vertices to their predecessors in the traversal tree
        """

        color_map = {}                  # maps vertices to their color
        distance_map = {}               # maps vertices to their distance from the start vertex
        predecessor_map = {}            # maps vertices to their predecessor in the traversal tree

        # Initialize the maps
        for vertex in self.all_vertices():
            color_map[vertex] = NodeColor.WHITE
            distance_map[vertex] = None
            predecessor_map[vertex] = None

        # Start at the given vertex
        start_node = self.get_vertex(start_name)
        color_map[start_node] = NodeColor.GRAY
        distance_map[start_node] = 0

        # Initialize the queue with the start vertex
        queue = deque()
        queue.append(start_node)

        # Process the queue
        while len(queue) > 0:
            vertex = queue.popleft()
            for dest in self.get_adjacent_vertices(vertex.value):
                if color_map[dest] == NodeColor.WHITE:
                    color_map[dest] = NodeColor.GRAY
                    distance_map[dest] = distance_map[vertex] + 1
                    predecessor_map[dest] = vertex
                    queue.append(dest)
            color_map[vertex] = NodeColor.BLACK

        # Return the distance and predecessor maps
        return distance_map, predecessor_map


    def path(self, destination, map):
        """
        Compute the path from the start vertex to the given destination vertex.
        The map parameter is the predecessor map
        """
        path = []
        destination_node = self.get_vertex(destination)
        while destination_node is not None:
            path.insert(0, destination_node.value)
            destination_node = map[destination_node]
        return path



class AdjacencyListGraph(Graph):
    """A graph implemented as an adjacency list."""
    def __init__(self):
        self.adjacency_map = {}     # maps vertex names to lists of adjacent vertices
        self.vertex_map = {}        # maps vertex names to vertices

    def insert_vertex(self, name: str):
        if name not in self.vertex_map:
            self.vertex_map[name] = Vertex(name)
        if name not in self.adjacency_map:
            self.adjacency_map[name] = []

    def connect(self, name1: str, name2: str, weight: float = 1):
        adjacency_list = self.adjacency_map[name1]
        dest = self.vertex_map[name2]
        adjacency_list.append((dest, weight))

    def all_vertices(self) -> List[Vertex]:
        return list(self.vertex_map.values())

    def get_vertex(self, name: str) -> Vertex:
        return self.vertex_map[name]

    def get_adjacent_vertices(self, name: str) -> List[Vertex]:
        return list(map(lambda x: x[0], self.adjacency_map[name]))

    def get_adjacent_vertices_with_weight(self, name: str) -> List[tuple[Vertex, float]]:
        return self.adjacency_map[name]




class AdjacencyMatrixGraph(Graph):
    """A graph implemented as an adjacency matrix."""
    def __init__(self):
        self.index_map = {}         # maps vertex names to indices
        self.vertex_list = []       # list of vertices
        self.adjacency_matrix = []  # adjacency matrix

    def insert_vertex(self, name: str):
        if name not in self.index_map:
            self.index_map[name] = len(self.vertex_list)
            self.vertex_list.append(Vertex(name))
            for row in self.adjacency_matrix:   # add a new column to each row
                row.append(None)
            self.adjacency_matrix.append([None] * len(self.vertex_list)) # add a new row

    def connect(self, name1: str, name2: str, weight: float = 1):
        index1 = self.index_map[name1]
        index2 = self.index_map[name2]
        self.adjacency_matrix[index1][index2] = weight

    def all_vertices(self) -> List[Vertex]:
        return self.vertex_list

    def get_vertex(self, name: str) -> Vertex:
        index = self.index_map[name]
        return self.vertex_list[index]

    def get_adjacent_vertices(self, name: str) -> List[Vertex]:
        index = self.index_map[name]
        result = []
        for i in range(len(self.vertex_list)):
            if self.adjacency_matrix[index][i] is not None:
                name = self.vertex_list[i].value
                result.append(self.get_vertex(name))
        return result

    def get_adjacent_vertices_with_weight(self, name: str) -> List[tuple[Vertex, float]]:
        index = self.index_map[name]
        result = []
        for i in range(len(self.vertex_list)):
            if self.adjacency_matrix[index][i] is not None:
                name = self.vertex_list[i].value
                result.append((self.get_vertex(name), self.adjacency_matrix[index][i]))
        return result






if __name__ == "__main__":

    def read_cave_into_graph(graph: Graph, filename: str):
        """Read a cave description from a file and insert it into the given graph."""
        with open(filename, "r") as file:
            lines = file.readlines()
            for line in lines:
                # match a line with two node names and an optional direction
                m = re.match(r"(^\s*\"(.*)\"\s*([<>]*)\s*\"(.*)\"\s*)", line)
                if m:
                    startnode = m.group(2)
                    endnode = m.group(4)
                    opcode = m.group(3)
                    graph.insert_vertex(startnode)
                    graph.insert_vertex(endnode)
                    if '>' in opcode:
                        graph.connect(startnode, endnode)
                    if '<' in opcode:
                        graph.connect(endnode, startnode)


    graph = AdjacencyListGraph()
    #graph = AdjacencyMatrixGraph()
    read_cave_into_graph(graph, "../../hoehle.txt")
    _, predecessor_map = graph.bfs('Höhleneingang')
    path = graph.path('Schatzkammer', predecessor_map)
    print(path)
    _, predecessor_map = graph.bfs('Schatzkammer')
    path = graph.path('Höhleneingang', predecessor_map)
    print(path)