如何解决如何在 Python 中为地球、月球和小行星（仅动画部分）的计算机模拟制作 Matplotlib 动画？？

我正在尝试对地球、月球和小行星绕太阳运行进行计算机模拟。

数据 r_earth、r_moon 和 r_asteroid 已经给出（它们是一个数组）。 xlim 和 ylim 太大了，因为我必须使用来自宇宙的真实值，否则我在动画上看不到任何东西。

import numpy as np

def RK4_step(y,t,f,dt):         #for numerical part I decided to use RK4 method
    k1 = dt * f(y,t)
    k2 = dt * f(y + 0.5 * k1,t + 0.5 * dt)
    k3 = dt * f(y + 0.5 * k2,t + 0.5 * dt)
    k4 = dt * f(y + k3,t + dt)

    return (t + dt,y + (k1 + 2. * (k2 + k3) + k4) / 6.)


def integrate_ode(y0,derivative_fn,step_fn,a,b,n):
    dt = (b - a) / (n - 1)
    t = a
    y = np.array(y0)

    res = [y]
    for _ in range(1,n):
        t,y = step_fn(y,dt)
        res.append(y)
    return (np.linspace(a,n),np.array(res))

# np.array(res) is 2D array of dimensions (<time steps>,<um variables>) that holds the values for each time step.

# Initial parameters for body masses(Sun,Earth,Moon,Asteroid)
G = 6.674e-11
m_s = 1.989e30
m_e = 5.972e24
m_m = 7.346e22
m_a = 1e25


def derivative_fn(y,t):                 # vectors necessary for 2.Newton''s Law
    d1 = y[1] - y[0]
    vec01 = d1 / np.linalg.norm(d1) ** 3
    d2 = y[2] - y[0]
    vec02 = d2 / np.linalg.norm(d2) ** 3
    d3 = y[2] - y[1]
    vec12 = d3 / np.linalg.norm(d3) ** 3

    der = np.array([
        y[3],y[4],y[5],- G * m_s * y[0] / np.linalg.norm(y[0]) ** 3 + G * m_m * vec01 + G * m_a * vec02,- G * m_s * y[1] / np.linalg.norm(y[1]) ** 3 - G * m_e * vec01 + G * m_a * vec12,- G * m_s * y[2] / np.linalg.norm(y[2]) ** 3 - G * m_e * vec02 - G * m_m * vec12])

    return der

# numerically computed data in the array form
# y = [r_e,r_m,r_a,v_e,v_m,v_a] -> 2D array of size (6,2)

# the initial distances between the bodies,# for Earth and Moon we compute it from 2nd Newton''s Law (orbital veLocity)
r_e0 = 1.519e11
v_e0 = np.sqrt(G * m_s / r_e0)
r_m0 = 1.521e11
v_m0 = np.sqrt(G * m_e / abs(r_m0 - r_e0))
r_a0 = 1e11
v_a0 = 31293  # m/s
y0 = np.array([[r_e0,0.],[r_m0,[r_a0,[0.,v_e0],v_e0 + v_m0],v_e0 + v_a0]])
# all the parameters are Now in the array y0,# the last two are veLocities relative to the Earth

n = 10000
ts,ys = integrate_ode(y0,RK4_step,0.,5.154e7,n)

r_earth = ys[:,:]
r_moon = ys[:,1,:]
r_asteroid = ys[:,2,:]

# Plotting

import matplotlib.pyplot as plt

plt.xlabel("x")
plt.ylabel("y")

plt.plot(r_earth[:,0],r_earth[:,1],label="Earth")
plt.plot(r_moon[:,r_moon[:,label="Moon")
plt.plot(r_asteroid[:,r_asteroid[:,label="Asteroid")

plt.show()

from matplotlib.animation import FuncAnimation

fig,ax = plt.subplots()
ax.set_xlim([-0.3e12,0.3e12])
ax.set_ylim([-0.3e12,0.3e12])

# xlim and ylim are so big because we wouldn''t see the animation.

sun,= ax.plot(0.,''oy'',ms=20)
earth,= ax.plot(r_earth[0,r_earth[0,''og'',ms=10)
moon,= ax.plot(r_moon[0,r_moon[0,''ob'',ms=3)
asteroid,= ax.plot(r_asteroid[0,r_asteroid[0,''ok'',ms=1)

num_frames = 10000
frame_duration = n / num_frames


def animation_frame(frame):
    index = int(frame_duration * frame)
    earth.set_data(r_earth[index,r_earth[index,1])
    moon.set_data(r_moon[index,0] / r_earth[index,r_moon[index,1] / r_earth[index,1])
    asteroid.set_data(r_asteroid[index,r_asteroid[index,1])

    return earth,moon,asteroid


animation = FuncAnimation(fig,func=animation_frame,frames=range(num_frames),interval=50)

plt.show()

当我开始编写代码时，月亮与太阳的位置相同，两者都是静态的。地球绕太阳运动的速度非常缓慢，动画中没有小行星。

如何解决这个问题？ 我仍然想使用真实数据，但希望动画速度快 100 倍（但动画仍然流畅）。我该怎么做？

解决方法

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import matplotlib.pyplot as plt
import numpy as np

# 在-1~1之间建立50个点
x = np.linspace(-1, 1, 50)
# y = 2*x + 1
y = x**2

# 创建画布
plt.plot(x, y)

# 展现画布
plt.show()

<dependency>
   <groupId>com.github.sh0nk</groupId>
       <artifactId>matplotlib4j</artifactId>
       <version>0.5.0</version>
</dependency>

 @Test
    public void testPlot() throws IOException, PythonExecutionException, ClassNotFoundException, NoSuchMethodException, illegalaccessexception, InvocationTargetException, InstantiationException {
        Plot plot = Plot.create(PythonConfig.pythonBinPathConfig("D:\\python3.6\\python.exe"));
        plt.plot()
                .add(Arrays.asList(1.3, 2))
                .label("label")
                .linestyle("--");
        plt.xlabel("xlabel");
        plt.ylabel("ylabel");
        plt.text(0.5, 0.2, "text");
        plt.title("Title!");
        plt.legend();
        plt.show();

    }

//拿到plotImpl中用于组装python脚本语句的的registeredBuilders，需要加什么直接添加新的builder就行了
        Field registeredBuildersField = plt.getClass().getDeclaredField("registeredBuilders");
        registeredBuildersField.setAccessible(true);
        List<Builder> registeredBuilders = (List<Builder>) registeredBuildersField.get(plt);

        TicksBuilder ticksBuilder = new TicksBuilder(yList, "yticks", fontSize);
        registeredBuilders.add(ticksBuilder);

import numpy as np
import matplotlib.pyplot as plt
plt.plot(np.array(自己的x数据), np.array(自己的y数据), 'k.', markersize=4)
plt.xlim(0,6000)
plt.ylim(0,24)
plt.yticks(np.arange(0, 25, 1), fontsize=10)
plt.title("waterfall")
plt.show()

		//1. 准备自己的数据 不用管
        List<Float> y_secondList_formatByHours = y_secondList.stream().map(second -> (float)second / 3600).collect(Collectors.toList());

        //2.准备命令行list，逐行命令添加
        List<String> scriptLines = new ArrayList<>();
        scriptLines.add("import numpy as np");
        scriptLines.add("import matplotlib.pyplot as plt");
        scriptLines.add("plt.plot("+"np.array("+x_positionList+"),"+"np.array(" +y_secondList_formatByHours+"),\"k.\",label=\"waterfall\",lw=1.0,markersize=4)");
        scriptLines.add("plt.xlim(0,6000)");
        scriptLines.add("plt.ylim(0,24)");
        scriptLines.add("plt.yticks(np.arange(0, 25, 1), fontsize=10)");
        scriptLines.add("plt.title(\"waterfall\")");
        scriptLines.add("plt.show()");
        //3. 调用matplotlib4j 里面的pycommond对象，传入自己电脑的python路径
        pycommand command = new pycommand(PythonConfig.pythonBinPathConfig("D:\\python3.6\\python.exe"));
        //4. 执行，每次执行会生成临时文件 如C:\Users\ADMINI~1\AppData\Local\Temp\1623292234356-0\exec.py，这个带的日志输出能看到，搞定
        command.execute(Joiner.on('\n').join(scriptLines));

import matplotlib.pyplot as plt
import matplotlib.animation as animation