我想以更好的方式设置模拟的动画：
a）目前的代码是模拟它们的轨道作为时间的函数。这真的是一些锯齿形的线在目前这是“丑陋”看。
B）我希望num_particles = 100在每一个时刻都是动画的。就像一个球在空间中移动。我不想跟踪它的轨迹/轨道。
c）所以在每个时间步，我应该只有我的num_particles作为云。
d）保存动画为mp4或类似文件。
我的模拟代码：

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.animation import FuncAnimation
# Constants
M_Sun = 1.989e30  # Solar Mass
M_bh = 4.3e6 *M_Sun #Mass of Sgr A*
G = 6.67430e-11  # m^3 kg^(-1) s^(-2)
yr = 365 * 24 * 60 * 60  # 1 year in seconds
R = 6.371e3 #Radius of Sphere
# Number of particles
num_particles = 100
#Uniformly distributed particles in Sphere of radius R
phi = np.random.uniform(0, 2*np.pi, size=num_particles)
costheta = np.random.uniform(-1, 1, size=num_particles)
u = np.random.uniform(0, 1, size=num_particles)
theta = np.arccos(costheta)
r = R * (u**(1/3))
x = r * np.sin(theta) * np.cos(phi)
y = r * np.sin(theta) * np.sin(phi)
z = r * np.cos(theta)
# Initial conditions for the particles (m and m/s)
initial_pos = np.random.uniform(0.8e13, 1.1e14, (num_particles, 3))
initial_vel = np.random.uniform(550e3, 730e3, (num_particles, 3))
# Steps
t_end = 1*yr # Total time of integration
dt_constant = 0.1
intervals = 1000000 # seconds after which to store pos & vel
next_interval_time = intervals
# Arrays to store pos and vel
pos = np.zeros((num_particles, 1, 3)) # shape: (#particles, timesteps taken, #coordinates)
vel = np.zeros((num_particles, 1, 3)) # shape: (#particles, timesteps taken, #coordinates)
# Initial conditions
time = np.zeros(1) # time array
pos[:, 0] = initial_pos
vel[:, 0] = initial_vel
pos_output = []
vel_output = []
t_output = []
while time[-1] <= t_end: # NOTE: We end up doing one more timestep after t_end
    r = np.linalg.norm(pos[:, -1], axis=1)
    acc = -G * M_bh / r[:, np.newaxis]**3 * pos[:, -1] #np.newaxis for broadcasting with pos[:, i-1]
    # Calculate the time step for the current particle
    current_dt = dt_constant * np.sqrt(np.linalg.norm(pos[:, -1], axis=1)**3 / (G * M_bh))
    min_dt = np.min(current_dt)  # Use the minimum time step for all particles
    # leap frog integration
    # calculate velocity at half timestep
    half_vel = vel[:, -1] + 0.5 * acc * min_dt
    # current position only used in this timestep
    _pos_t = pos[:, -1] + half_vel * min_dt # shape: (#particles, #coordinates)
    # Recalculate acceleration with the new position
    r = np.linalg.norm(_pos_t, axis=1)
    # Acceleration at timestep
    acc = -G * M_bh / r[:, np.newaxis]**3 * _pos_t #np.newaxis for broadcasting with pos[:, i-1]
    # current velocity only used in this timestep
    _vel_t = half_vel + 0.5 * acc * min_dt # shape: (#particles, #coordinates)
    
    # time at timestep t
    _time_t = time[-1] + min_dt
   # Check if the elapsed time has surpassed the next interval
    if _time_t >= next_interval_time:
        pos_output.append(_pos_t.copy())
        vel_output.append(_vel_t.copy())
        t_output.append(_time_t.copy())
        next_interval_time += intervals
    # add axis at position 1 to allow concatenation
    pos = np.concatenate((pos, _pos_t[:, np.newaxis]), axis=1)
    vel = np.concatenate((vel, _vel_t[:, np.newaxis]), axis=1)
    time = np.append(time, _time_t)
# show current status by printing timestep number (-1 because initial conditions)
    print(f'timestep: {time.size -1} [progress: {_time_t/t_end*100:.3f}%]')
pos_output = np.array(pos_output).transpose((1, 0, 2)) # shape: (#objects, #stored timesteps, #coordinates)
np.save('pos_output.npy', pos_output)
vel_output = np.array(vel_output).transpose((1, 0, 2)) # shape: (#objects, #stored timesteps, #coordinates)
np.save('vel_output.npy', vel_output)
t_output = np.array(t_output)
np.save('t_output.npy', t_output)
print(pos_output.shape)
print(vel_output.shape)
print(t_output.shape)
#ANIMATION
from orbit_animation import animate_orbits
animate_orbits(pos_output)

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我的动画代码：

# orbit_animation.py
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.animation import FuncAnimation
def animate_orbits(pos, intervals=1000000, interval=500):
    fig = plt.figure(figsize=(8, 8))
    ax = fig.add_subplot(111, projection='3d')
    # Scatter plot for Sgr A*
    sgr_a_plot = ax.scatter([0], [0], [0], color='black', marker='o', s=50, label='Sgr A*')
    # Initialize an empty line for the cloud particles
    cloud_plot, = ax.plot([], [], [], label='Cloud Particles')
    # Set plot labels and title
    ax.set_xlabel('X (km)')
    ax.set_ylabel('Y (km)')
    ax.set_zlabel('Z (km)')
    ax.legend(loc='upper right', bbox_to_anchor=(1.1, 1.1))
    ax.set_title('Orbits of cloud particles around Sgr A*')
    # Initialize axis limits
    x_min, x_max = np.min(pos[:, :, 0]), np.max(pos[:, :, 0])
    y_min, y_max = np.min(pos[:, :, 1]), np.max(pos[:, :, 1])
    z_min, z_max = np.min(pos[:, :, 2]), np.max(pos[:, :, 2])
    # Animation update function
    def update(frame):
        # Update Sgr A* position
        sgr_a_plot._offsets3d = ([0], [0], [0])
        # Update cloud particles
        cloud_plot.set_data(pos[:, frame, 0], pos[:, frame, 1])
        cloud_plot.set_3d_properties(pos[:, frame, 2])
        # Update axis limits dynamically
        x_min, x_max = np.min(pos[:, :, 0]), np.max(pos[:, :, 0])
        y_min, y_max = np.min(pos[:, :, 1]), np.max(pos[:, :, 1])
        z_min, z_max = np.min(pos[:, :, 2]), np.max(pos[:, :, 2])
        ax.set_xlim(x_min, x_max)
        ax.set_ylim(y_min, y_max)
        ax.set_zlim(z_min, z_max)
        return sgr_a_plot, cloud_plot
    # Create the animation
    animation = FuncAnimation(fig, update, frames=pos.shape[1], interval=interval, blit=True)
    plt.show()

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我希望我能解释我在这里试图实现什么！提前感谢您的帮助！