binary_search_tree.py

@@ -1,102 +0,0 @@
-
-class Node:
-    def __init__(self, key):
-        self.key = key
-        self.left = None
-        self.right = None
-
-# Inorder traversal
-def inorder(root):
-    if root is not None:
-        # Traverse left
-        inorder(root.left)
-
-        # Traverse root
-        print(str(root.key) + "->", end=' ')
-
-        # Traverse right
-        inorder(root.right)
-
-
-# Insert a node
-def insert(node, key):
-
-    # Return a new node if the tree is empty
-    if node is None:
-        return Node(key)
-
-    # Traverse to the right place and insert the node
-    if key < node.key:
-        node.left = insert(node.left, key)
-    else:
-        node.right = insert(node.right, key)
-
-    return node
-
-
-# Find the inorder successor
-def minValueNode(node):
-    current = node
-
-    # Find the leftmost leaf
-    while(current.left is not None):
-        current = current.left
-
-    return current
-
-
-# Deleting a node
-def deleteNode(root, key):
-
-    # Return if the tree is empty
-    if root is None:
-        return root
-
-    # Find the node to be deleted
-    if key < root.key:
-        root.left = deleteNode(root.left, key)
-    elif(key > root.key):
-        root.right = deleteNode(root.right, key)
-    else:
-        # If the node is with only one child or no child
-        if root.left is None:
-            temp = root.right
-            root = None
-            return temp
-
-        elif root.right is None:
-            temp = root.left
-            root = None
-            return temp
-
-        # If the node has two children,
-        # place the inorder successor in position of the node to be deleted
-        temp = minValueNode(root.right)
-
-        root.key = temp.key
-
-        # Delete the inorder successor
-        root.right = deleteNode(root.right, temp.key)
-
-    return root
-
-
-root = None
-root = insert(root, 9)
-root = insert(root, 3)
-root = insert(root, 2)
-root = insert(root, 4)
-root = insert(root, 7)
-root = insert(root, 10)
-root = insert(root, 15)
-root = insert(root, 5)
-
-print("Inorder traversal: ", end=' ')
-inorder(root)
-
-print("\nDelete 10")
-root = deleteNode(root, 10)
-
-print("Inorder traversal: ", end=' ')
-inorder(root)
-    

binary_tree.py

@@ -1,46 +0,0 @@
-
-class Node:
-    def __init__(self, key):
-        self.left = None
-        self.right = None
-        self.val = key
-
-    # Traverse preorder
-    def traversePreOrder(self):
-        print(self.val, end=' ')
-        if self.left:
-            self.left.traversePreOrder()
-        if self.right:
-            self.right.traversePreOrder()
-
-    # Traverse inorder
-    def traverseInOrder(self):
-        if self.left:
-            self.left.traverseInOrder()
-        print(self.val, end=' ')
-        if self.right:
-            self.right.traverseInOrder()
-
-    # Traverse postorder
-    def traversePostOrder(self):
-        if self.left:
-            self.left.traversePostOrder()
-        if self.right:
-            self.right.traversePostOrder()
-        print(self.val, end=' ')
-
-
-root = Node(5)
-
-root.left = Node(6)
-root.right = Node(7)
-
-root.left.left = Node(8)
-
-print("Preorder Traversal: ", end="")
-root.traversePreOrder()
-print("\nInorder Traversal: ", end="")
-root.traverseInOrder()
-print("\nPostorder Traversal: ", end="")
-root.traversePostOrder()
-    

graph.py

@@ -1,40 +0,0 @@
-class Graph:
-    def __init__(self):
-        self.graph = {}
-        
-    def add_vertex(self, vertex):
-        if vertex not in self.graph:
-            self.graph[vertex] = []
-        else:
-            print(f"Vertex {vertex} already exists.")
-            
-    def add_edge(self, vertex1, vertex2, length:int):
-        if vertex1 in self.graph and vertex2 in self.graph:
-            self.graph[vertex1].append(vertex2)
-            self.graph[vertex2].append(vertex1)
-            self.length = length
-        else:
-            print("One or both vertices not found.")
-    
-    def display(self):
-        for vertex in self.graph:
-            print(f'{vertex}: {self.graph[vertex]} : {self.length}' )
-
-# Example usage
-if __name__ == "__main__":
-    g = Graph()
-    
-    # Adding vertices
-    g.add_vertex("A")
-    g.add_vertex("B")
-    g.add_vertex("C")
-    g.add_vertex("D")
-    
-    # Adding edges
-    g.add_edge("A", "B", 10)
-    g.add_edge("A", "C", 5)
-    g.add_edge("B", "D", 30)
-    g.add_edge("C", "D", 11)
-    
-    # Display the graph
-    g.display()

graph_with_edge_lengths.py

@@ -1,90 +0,0 @@
-import heapq
-
-class Graph:
-    def __init__(self):
-        self.graph = {}              # adjacency list
-        self.edge_lengths = {}       # edge length dictionary
-
-    def add_vertex(self, vertex):
-        if vertex not in self.graph:
-            self.graph[vertex] = []
-        else:
-            print(f"Vertex {vertex} already exists.")
-
-    def add_edge(self, vertex1, vertex2, length: float):
-        if vertex1 in self.graph and vertex2 in self.graph:
-            self.graph[vertex1].append(vertex2)
-            self.graph[vertex2].append(vertex1)
-            # Store edge length using a frozenset to avoid duplicates
-            self.edge_lengths[frozenset([vertex1, vertex2])] = length
-        else:
-            print("One or both vertices not found.")
-
-    def display(self):
-        print("Adjacency List:")
-        for vertex in self.graph:
-            print(f'{vertex}: {self.graph[vertex]}')
-        print("\nEdge Lengths:")
-        for edge, length in self.edge_lengths.items():
-            v1, v2 = tuple(edge)
-            print(f'{v1} - {v2}: {length}')
-            
-
-    def dijkstra(self, start, end):
-        distances = {vertex: float('inf') for vertex in self.graph}
-        distances[start] = 0
-        previous = {vertex: None for vertex in self.graph}
-        queue = [(0, start)]
-
-        while queue:
-            current_distance, current_vertex = heapq.heappop(queue)
-
-            if current_vertex == end:
-                break
-
-            for neighbor in self.graph[current_vertex]:
-                edge = frozenset([current_vertex, neighbor])
-                weight = self.edge_lengths.get(edge, float('inf'))
-                distance = current_distance + weight
-
-                if distance < distances[neighbor]:
-                    distances[neighbor] = distance
-                    previous[neighbor] = current_vertex
-                    heapq.heappush(queue, (distance, neighbor))
-
-        # Reconstruct path
-        path = []
-        current = end
-        while current:
-            path.insert(0, current)
-            current = previous[current]
-
-        print(f"Shortest path from {start} to {end}: {' -> '.join(path)} with length {distances[end]}")
-            
-# Example usage
-g = Graph()
-
-# City node abbreviations
-A = "San Tan Valley"
-B = "Phoenix"
-C = "Globe"
-D = "Mesa"
-E = "Florence"
-
-# Adding nodes to graph
-g.add_vertex(A)
-g.add_vertex(B)
-g.add_vertex(C)
-g.add_vertex(D)
-g.add_vertex(E)
-
-# Adding edges to graph
-g.add_edge(A, B, 34)
-g.add_edge(A, C, 47)
-g.add_edge(B, D, 18.8)
-g.add_edge(C, D, 13)
-g.add_edge(B, E, 63)
-
-g.display()
-g.dijkstra(A, D)
-