پروژه پایتون (فناوری اطلاعات)

کارشناسی ارشد مهندسی فناوری اطلاعات من یک پایان نامه با مشخصات زیر دارم ،میخواستم ببینید هزینه اینکه کد من درست کار میکند یا خیر چقدر است ؟ (ضمیمه کردم) پروژه پایتون: Station') plt.title("Loyal LEACH - WSN Simulation") plt.xlabel("X-axis") plt.ylabel("Y-axis") plt.legend() plt.grid() plt.show() import numpy as np import matplotlib.pyplot as plt # Parameters NUM\_NODES = 100  # Number of nodes FIELD\_SIZE = (100, 100)  # Area of the network (100x100 units) INITIAL\_ENERGY = 0.5  # Initial energy for each node (in Joules) BASE\_STATION = (50, 50)  # Location of the base station TRANSMIT\_COST = 50e-9  # Energy to transmit (per bit) RECEIVE\_COST = 50e-9  # Energy to receive (per bit) AMPLIFICATION\_COST = 10e-12  # Energy for amplification (per bit per meter^2) DATA\_PACKET\_SIZE = 4000  # Packet size in bits LOYALITY\_THRESHOLD = 5  # Number of rounds a node avoids being a cluster head # Node Class class Node:     def \_init\_(self, x, y):         self.x = x         self.y = y         self.energy = INITIAL\_ENERGY         self.is\_cluster\_head = False         self.cluster = None         self.rounds\_since\_ch = 0  # Tracks rounds since last CH status     def distance\_to(self, x, y):         return np.sqrt((self.x - x)\*2 + (self.y - y)\*2) # Initialize nodes nodes = \[Node(np.random.uniform(0, FIELD\_SIZE\[0\]), np.random.uniform(0, FIELD\_SIZE\[1\])) for \_ in range(NUM\_NODES)\] # Loyal LEACH Algorithm def select\_cluster\_heads(nodes, p=0.1):     """Select cluster heads based on energy and loyalty constraints."""     for node in nodes:         if (             node.energy > 0 and             node.rounds\_since\_ch >= LOYALITY\_THRESHOLD and             np.random.rand() < p and             node.energy > np.mean(\[n.energy for n in nodes if n.energy > 0\])         ):             node.is\_cluster\_head = True             node.rounds\_since\_ch = 0         else:             node.is\_cluster\_head = False             node.rounds\_since\_ch += 1 def assign\_clusters(nodes):     """Assign nodes to the nearest cluster head."""     for node in nodes:         if not node.is\_cluster\_head and node.energy > 0:             min\_dist = float('inf')             for ch in \[n for n in nodes if n.is\_cluster\_head and n.energy > 0\]:                 dist = node.distance\_to(ch.x, ch.y)                 if dist < min\_dist:                     min\_dist = dist                     node.cluster = ch # Energy Consumption def transmit(node, distance):     """Calculate energy consumption for transmission."""     return TRANSMIT\_COST \* DATA\_PACKET\_SIZE + AMPLIFICATION\_COST \* DATA\_PACKET\_SIZE \* distance\*\*2 def receive():     """Calculate energy consumption for receiving."""     return RECEIVE\_COST \* DATA\_PACKET\_SIZE # Simulation NUM\_ROUNDS = 100 total\_energy\_consumed = 0 packets\_to\_base\_station = 0 for round\_num in range(NUM\_ROUNDS):     print(f"Round {round\_num + 1}")     # Select cluster heads     select\_cluster\_heads(nodes)     # Assign clusters     assign\_clusters(nodes)     # Energy consumption for cluster communication     for node in nodes:         if node.energy > 0:             if node.is\_cluster\_head:                 # Cluster heads receive and transmit                 total\_receive\_cost = sum(receive() for n in nodes if n.cluster == node)                 distance\_to\_bs = node.distance\_to(\*BASE\_STATION)                 transmit\_cost = transmit(node, distance\_to\_bs)                 node.energy -= total\_receive\_cost + transmit\_cost                 total\_energy\_consumed += total\_receive\_cost + transmit\_cost                 packets\_to\_base\_station += 1             elif node.cluster:                 # Regular nodes transmit to cluster head                 distance\_to\_ch = node.distance\_to(node.cluster.x, node.cluster.y)                 transmit\_cost = transmit(node, distance\_to\_ch)                 node.energy -= transmit\_cost                 total\_energy\_consumed += transmit\_cost     # Remove nodes with no energy     alive\_nodes = sum(1 for node in nodes if node.energy > 0)     print(f"Alive nodes: {alive\_nodes}") # Plot plt.figure(figsize=(8, 8)) for node in nodes:     if node.energy > 0:         color = 'red' if node.is\_cluster\_head else 'blue'         plt.scatter(node.x, node.y, color=color)     else:         plt.scatter(node.x, node.y, color='black') plt.scatter(BASE\_STATION\[0\], BASE\_STATION\[1\], color='green', marker='x', label='Base داده ها همینقدر است