task_4.py

import uuid
import networkx as nx
import matplotlib.pyplot as plt
import heapq

class Node:
    def __init__(self, key, color="skyblue"):
        self.left = None
        self.right = None
        self.val = key
        self.color = color
        self.id = str(uuid.uuid4())

def add_edges(graph, node, pos, x=0, y=0, layer=1):
    if node is not None:
        graph.add_node(node.id, color=node.color, label=node.val)
        if node.left:
            graph.add_edge(node.id, node.left.id)
            l = x - 1 / 2 ** layer
            pos[node.left.id] = (l, y - 1)
            l = add_edges(graph, node.left, pos, x=l, y=y - 1, layer=layer + 1)
        if node.right:
            graph.add_edge(node.id, node.right.id)
            r = x + 1 / 2 ** layer
            pos[node.right.id] = (r, y - 1)
            r = add_edges(graph, node.right, pos, x=r, y=y - 1, layer=layer + 1)
    return graph

def draw_tree(tree_root):
    tree = nx.DiGraph()
    pos = {tree_root.id: (0, 0)}
    tree = add_edges(tree, tree_root, pos)

    colors = [node[1]['color'] for node in tree.nodes(data=True)]
    labels = {node[0]: node[1]['label'] for node in tree.nodes(data=True)}

    plt.figure(figsize=(8, 5))
    nx.draw(tree, pos=pos, labels=labels, arrows=False, node_size=2500, node_color=colors)
    plt.show()

def heapify(arr):
    heap = []
    for val in arr:
        heapq.heappush(heap, val)
    return heap

def build_heap_tree(heap):
    if not heap:
        return None
    root = Node(heap[0])
    queue = [root]
    i = 1
    while i < len(heap):
        node = queue.pop(0)
        if i < len(heap):
            node.left = Node(heap[i])
            queue.append(node.left)
            i += 1
        if i < len(heap):
            node.right = Node(heap[i])
            queue.append(node.right)
            i += 1
    return root

# Example usage:
arr = [10, 5, 3, 2, 1]
heap = heapify(arr)
root = build_heap_tree(heap)
draw_tree(root)