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Anna Morón

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generate functionSun, 20 Apr 2025

Funció: Crear un graf que representi les relacions entre els nois. Descripció: Els nodes del graf representaran els nois. Les arestes representaran les restriccions: per exemple, si un noi no pot estar darrere del seu enemic sense que abans hi hagi el seu amic, això es traduirà en una restricció d'ordre entre els nodes.

Per crear un graf que representi les relacions entre els nois, podem utilitzar la biblioteca `networkx` per crear el graf i `matplotlib` per visualitzar-lo. A continuació, hi ha un exemple de com fer-ho: ```python import networkx as nx import matplotlib.pyplot as plt # Crear un graf nou G = nx.DiGraph() # Afegir nodes (nois) G.add_node("Joan") G.add_node("Pere") G.add_node("Lluís") G.add_node("Marc") # Afegir arestes (restriccions) # Joan no pot estar darrere de Pere sense que abans hi hagi Lluís G.add_edge("Lluís", "Pere") G.add_edge("Lluís", "Joan") # Pere no pot estar darrere de Marc sense que abans hi hagi Joan G.add_edge("Joan", "Marc") G.add_edge("Joan", "Pere") # Marc no pot estar darrere de Lluís sense que abans hi hagi Pere G.add_edge("Pere", "Lluís") G.add_edge("Pere", "Marc") # Visualitzar el graf pos = nx.spring_layout(G) nx.draw_networkx_nodes(G, pos, node_size=500, node_color='lightblue') nx.draw_networkx_labels(G, pos, font_size=10) nx.draw_networkx_edges(G, pos, edge_color='gray', arrowsize=20) plt.show() ``` En aquest exemple, els nodes representen els nois i les arestes representen les restriccions. Les arestes són direccions, per exemple, si hi ha una aresta de "Lluís" a "Pere", significa que Lluís ha de venir abans que Pere. Per visualitzar el graf, es crea un layout amb `spring_layout` i es dibuixen els nodes i les arestes amb `draw_networkx_nodes`, `draw_networkx_labels` i `draw_networkx_edges`. Finalment, es mostra el graf amb `plt.show()`.

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generate functionSun, 20 Apr 2025

This function will process each line of the input file, where each line contains three names: the boy, his enemy, and his best friend. The data will be stored in a suitable structure (such as a dictionary or a list of tuples) for further processing.

Here's a Python function that reads the input file and stores the data in a dictionary where the keys are the boy's names and the values are dictionaries containing the enemy's name and the best friend's name. ```python def process_file(file_path): """ Process each line of the input file and store the data in a dictionary. Args: file_path (str): The path to the input file. Returns: dict: A dictionary where the keys are the boy's names and the values are dictionaries containing the enemy's name and the best friend's name. """ data = {} try: with open(file_path, 'r') as file: for line in file: # Remove leading and trailing whitespaces line = line.strip() # Split the line into three names boy, enemy, best_friend = line.split(',') # Store the data in the dictionary data[boy] = {'enemy': enemy, 'best_friend': best_friend} except FileNotFoundError: print(f"File {file_path} not found.") except Exception as e: print(f"An error occurred: {e}") return data # Example usage: file_path = 'input.txt' # Replace with your input file path data = process_file(file_path) print(data) ``` In this code: 1. We define a function `process_file` that takes the file path as an argument. 2. We open the file in read mode (`'r'`) using a `with` statement, which ensures the file is properly closed after we're done with it. 3. We iterate over each line in the file, remove leading and trailing whitespaces, and split the line into three names using the `split` method with a comma as the separator. 4. We store the data in a dictionary where the keys are the boy's names and the values are dictionaries containing the enemy's name and the best friend's name. 5. We handle potential exceptions, such as a `FileNotFoundError` if the file does not exist, and print an error message if an exception occurs. 6. Finally, we return the dictionary containing the processed data. You can replace `'input.txt'` with the path to your input file and run the code to process the file and store the data in a dictionary.

Python
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generate functionSun, 20 Apr 2025

Function: Verify that the enmity and friendship relationships are consistent with the bragging order. Description: This function will verify that: A guy's enemy is always someone with a higher bragging degree (except for the first guy, who can have any enemy). There are no contradictions such as enmity cycles or invalid relationships that make it impossible to find a solution.

```python from collections import defaultdict, deque def verify_relationships(bragging_order, relationships): """ Verify that the enmity and friendship relationships are consistent with the bragging order. Args: bragging_order (list): A list of integers representing the bragging order of guys. relationships (dict): A dictionary where each key is a guy and the value is a list of his enemies. Returns: bool: True if the relationships are consistent with the bragging order, False otherwise. """ # Create a graph from the relationships graph = defaultdict(list) for guy, enemies in relationships.items(): for enemy in enemies: graph[guy].append(enemy) # Check for enmity cycles for guy in graph: visited = set() stack = deque([guy]) while stack: current_guy = stack.pop() if current_guy in visited: return False # Enmity cycle detected visited.add(current_guy) for enemy in graph[current_guy]: if enemy not in visited: stack.append(enemy) # Check that a guy's enemy is always someone with a higher bragging degree for guy, enemies in relationships.items(): for enemy in enemies: if bragging_order.index(guy) >= bragging_order.index(enemy): return False # Enemy has a lower or equal bragging degree return True # Example usage: bragging_order = [1, 2, 3, 4] relationships = { 1: [2], 2: [3], 3: [4], 4: [] } print(verify_relationships(bragging_order, relationships)) # Output: True ``` This function first creates a graph from the relationships, where each guy is a node and his enemies are the edges connecting to that node. It then checks for enmity cycles by performing a depth-first search (DFS) on the graph. If a cycle is detected, the function returns False. Next, it checks that a guy's enemy is always someone with a higher bragging degree by iterating over the relationships and checking the bragging order of each guy and his enemies. If it finds a guy whose enemy has a lower or equal bragging degree, it returns False. If the function completes without finding any issues, it returns True, indicating that the relationships are consistent with the bragging order.

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