Write a Java Program representing the below graph. The vertices should be represented using array. Edges should be represented using three ways: 2D array, edge objects and an adjacency matrix.

1. Given a Vertex object x, give Java code to enumerate its outgoing edges. ("Enumerate" means "to list"; your code does not need to do anything with the edges, but should be setup code that would make it easy to do something with each edge if we wanted to add that in.) 2. Given a VertexAndDist object x and a new distance d, give Java code to create an updated object with the same vertex as x but with distance d. 3. For simplicity of implementation, we use HashMaps to map vertices to handles/parents and edges to weights. How could you modify the Vertex and/or Edge classes, as well as the maps themselves, to implement the maps using ordinary arrays, with no hashing? Be sure to address both the vertex and edge maps in your answer. (Hint: consider the Vertex's "id" field for inspiration.)

Consider the following method. /** Postcondition: m is displayed in a rectangular matrix for example: 1 2 3 4 5 6 7 8 public static void displayMatrix (int [] [] m) for (int r = 0; r < m.length; r++) for (int c = 0; c < m.length; c++) System.out.print (m[r] [c] + " "); System.out.println (); Will method displayMatrixsatisfy its postcondition? Yes, but only if the row-size and col-size are identical, No, all the numbers will display in one column. Yes, all the numbers will display in a correct rectangular display. No, because the code will generate an IndexArrayoutofBoundsException error. No, all the numbers will display in one row. ОООО О

Given the weightedGraph class below, implement the Bellman Ford and Dijkstra's algorithms following the instructions in the comments of the screenshots provided. This should be completed in python 3.10 or later please.  class WeightedGraph(Graph) :    """Weighted graph represented with adjacency lists."""     def __init__(self, v=10, edges=[], weights=[]) :        """Initializes a weighted graph with a specified number of vertexes.         Keyword arguments:        v - number of vertexes        edges - any iterable of ordered pairs indicating the edges         weights - list of weights, same length as edges list        """        super().__init__(v)        for i, (u, v) in enumerate(edges):            self.add_edge(u, v, weights[i])                    def add_edge(self, a, b, w=1) :        """Adds an edge to the graph.         Keyword arguments:        a - first end point        b - second end point        """        self._adj[a].add(b, w)        self._adj[b].add(a, w)     def…

java          (1) Implement the function by allocating a new n X n 2D array. Then write the rotation to it by writing the rows of the original matrix to the columns in the solution matrix such that they fit the solution require[1]ment. Then copy the new matrix exactly the same to the original matrix so that you know for sure you have updated the original matrix to look modified. (2) Implement the function by not allocating a new n X n 2D array. Hint : Perform the rotation in a layer by layer fashion - meaning - different layers can be processed independently. Also within a layer, you can exchange groups of four elements at a time to perform the rotation. Example : Send 1 to 4’s location, 4 to 16’s location, 16 to 13’s location and 13 to 1’s location. Ungraded but Important : As a comment in your code for Problem 2, write your observation on the different solutioning methods utilized. should speak in terms of Time and Space Complexity. Which solution does what in terms of time and…

Please follow the instructions in the screenshots provided and use that to implement the code given below. Done in python 3.10 or later please.    class WeightedAdjacencyMatrix :    """A weighted graph represented as a matrix."""     __slots__ = ['_W']     def __init__(self, size, edges=[], weights=[]) :        """Initializes a weighted adjacency matrix for a graph with size nodes.         Graph is initialized with size nodes and a specified set of        edges and edge weights.                Keyword arguments:        size -- Number of nodes of the graph.        edges -- a list of ordered pairs (2-tuples) indicating the                 edges of the graph.  The default value is an empty list                 which means no edges by default.        weights -- a list of weights for the edges, which should be the same                   length as the edges list.  The position of a value in                   the weights list corresponds to the edge in the same                   position of…