i have a code of visualization of neural network, but part of pygame is not full. there is not bullet, there is not bullet range, bullet speed etc.


import numpy as np
import random
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense


# Constants
GAME_AREA_WIDTH = 1000
GAME_AREA_HEIGHT = 1000


# Random enemy movement
def update_enemy_position(enemy_pos, enemy_vel):
    new_pos_x = enemy_pos[0] + enemy_vel[0]
    new_pos_y = enemy_pos[1] + enemy_vel[1]
    return new_pos_x, new_pos_y


def random_velocity():
    speed = random.uniform(3, 10)
    angle = random.uniform(0, 2 * np.pi)
    vel_x = speed * np.cos(angle)
    vel_y = speed * np.sin(angle)
    return vel_x, vel_y


# Neural network
input_neurons = 9 # Including the enemy velocities (2 additional inputs)
output_neurons = 2


model = Sequential()
model.add(Dense(32, activation='relu', input_dim=input_neurons))
model.add(Dense(64, activation='relu'))
model.add(Dense(output_neurons))


model.compile(optimizer='adam', loss='mse', metrics=['accuracy'])


# Input: bullet speed, bullet range, player x, player y, enemy x, enemy y, enemy velocity x, enemy velocity y
def desired_joystick_coords(player_pos, enemy_pos, enemy_vel, bullet_speed, bullet_range):
    time_to_hit = bullet_range / bullet_speed
    
    future_enemy_pos = enemy_pos
    for _ in range(int(time_to_hit)):
        future_enemy_pos = update_enemy_position(future_enemy_pos, enemy_vel)
        enemy_vel = random_velocity() # Update enemy velocity to create unpredictable movements


    joystick_x = future_enemy_pos[0] - player_pos[0]
    joystick_y = future_enemy_pos[1] - player_pos[1]
    return joystick_x, joystick_y


def generate_training_data(num_samples):
    training_data = []


    for _ in range(num_samples):
        bullet_speed = random.uniform(50, 200)
        bullet_range = random.uniform(100, 500)
        player_pos = (random.randint(0, GAME_AREA_WIDTH), random.randint(0, GAME_AREA_HEIGHT))
        enemy_pos = (random.randint(0, GAME_AREA_WIDTH), random.randint(0, GAME_AREA_HEIGHT))
        enemy_vel = random_velocity()
        step = random.randint(0, 100)


        desired_coords = desired_joystick_coords(player_pos, enemy_pos, enemy_vel, bullet_speed, bullet_range)
        input_data = (bullet_speed, bullet_range, player_pos[0], player_pos[1], enemy_pos[0], enemy_pos[1], enemy_vel[0], enemy_vel[1], step)
        output_data = desired_coords
        training_data.append((input_data, output_data))
    
    return training_data
'''
# Generate and prepare training data
num_samples = 10000
raw_training_data = generate_training_data(num_samples)
X, y = zip(*raw_training_data)


# Train the neural network
model.fit(np.array(X), np.array(y), epochs=10000, validation_split=0.2)
model.save('my_model3.h5')'''


import pygame
from tensorflow.keras.models import load_model


# Load the trained model
model = load_model('my_model3.h5')


# Pygame setup
pygame.init()
screen = pygame.display.set_mode((GAME_AREA_WIDTH, GAME_AREA_HEIGHT))
pygame.display.set_caption('Pygame Visualization')
clock = pygame.time.Clock()


# Colors
WHITE = (255, 255, 255)
RED = (255, 0, 0)
GREEN = (0, 255, 0)


# Player and enemy positions
player_pos = (GAME_AREA_WIDTH // 2, GAME_AREA_HEIGHT // 2)
enemy_pos = (random.randint(0, GAME_AREA_WIDTH), random.randint(0, GAME_AREA_HEIGHT))
enemy_vel = random_velocity()


# Bullet properties
bullet_speed = 50
bullet_range = 100


running = True
while running:
    screen.fill(WHITE)


    # Draw player and enemy
    pygame.draw.circle(screen, RED, player_pos, 10)
    pygame.draw.circle(screen, GREEN, enemy_pos, 10)


    # Get joystick coordinates from the neural network
    input_data = np.array([bullet_speed, bullet_range, player_pos[0], player_pos[1], enemy_pos[0], enemy_pos[1], enemy_vel[0], enemy_vel[1], 0]).reshape(1, -1)
    joystick_coords = model.predict(input_data)[0]


    # Draw bullet trajectory
    pygame.draw.line(screen, (0, 0, 255), player_pos, (player_pos[0] + joystick_coords[0], player_pos[1] + joystick_coords[1]), 2)


    # Update enemy position
    enemy_pos = update_enemy_position(enemy_pos, enemy_vel)
    enemy_vel = random_velocity()


    # Check for quit event
    for event in pygame.event.get():
        if event.type == pygame.QUIT:
            running = False


    pygame.display.flip()
    clock.tick(60)


pygame.quit()