用python画一个平面的太阳系得到一些朋友的欣赏,然后有同学提出了绘制三维太阳系编程客栈的要求。
从Python画图的角度来说,三维太阳系其实并不难,问题在于八大行星对黄道面的倾斜太小,所以尽管画个三维的图,但就观感而言,无非是把二维的嵌入到三维空间罢了。
来点小行星
代码如下
from os import cpu_count import numpy as np from numpy.random import rand import matplotlib.pyplot as plt from matplotlib import animation au,G,RE,ME = 1.48e11,6.67e-11,1.48e11,5.965e24 m = np.array([3.32e5,0.055,0.815,1,0.107,317.8])*ME*G r = np.array([0,0.387,0.723,1,1.524,5.203])*RE v = np.array([0,47.89,35.03,29.79,24.13,13.06])*1000 theta = rand(len(m))*np.pi*2 cTheta,sTheta = np.cos(theta), np.sin(theta) xywww.cppcns.comz =编程客栈 r*np.array([cTheta, sTheta, 0*r]) #位置三分量,因为参数太多,所以把这三个分量写在了一起 uvw = v*np.array([-sTheta, cTheta, 0*v]) #速度三分量 N_ast = 100 m_ast = rand(N_ast)*1e20 r_ast = (rand(N_ast)*3.5+1.6)*RE v_ast = np.sqrt(G*3.32e5*ME/r_ast) #小行星速度sqrt(GM/R) theta = rand(N_ast)*np.pi*2 phi = (rand(N_ast)-0.5)*0.3 #给一个随机的小倾角 cTheta,sTheta = np.cos(theta), np.sin(theta) cPhi,sPhi = np.cos(phi),np.sin(phi) xyza = r_ast*np.array([cTheta*cPhi, sTheta*cPhi, sPhi]) uvwa = v_ast*np.array([-sTheta*cPhi, cTheta*cPhi, sPhi]) name = "solar.gif" fig = plt.figure(figsize=(10,10)) ax = fig.add_subplot(projection='3d') ax.grid() ax.set_xlim3d([-5.5*REwww.cppcns.com,5.5*RE]) ax.set_ylim3d([-5.5*RE,5.5*RE]) ax.set_zlim3d([-5.5*RE,5.5*RE]) traces = [ax.plot([],[],[],'-', lw=0.5)[0] for _ in range(len(m))] pts = [ax.plot([],[],[],marker='o')[0] for _ in range(len(m))] pt_asts = [ax.plot([],[],[],marker='.')[0] for _ in range(N_ast)] N = 500 dt = 3600*50 ts = np.arange(0,N*dt,dt) xyzs,xyzas = [],[] for _ in ts: xyz_ij = (xyz.reshape(3,1,len(m))-xyz.reshape(3,len(m),1)) r_ij = np.sqrt(np.sum(xyz_ij**2,0)) xyza_ij = (xyz.reshape(3,1,len(m))-xyza.reshape(3,N_ast,1)) ra_ij = np.sqrt(np.sum(xyza_ij**2,0)) for j in range(len(m)): for i in range(len(m)): if i!=j : uvw[:,i] += m[j]*xyz_ij[:,i,j]*dt/r_ij[i,j]**3 for i in range(N_ast): uvwa[:,i] += m[j]*xyza_ij[:,uknpKeAOi,j]*dt/ra_ij[i,j]**3 xyz += uvw*dt xyza += uvwa*dt xyzs.append(xyz.tolist()) xyzas.append(xyza.tolist()) xyzs = np.array(xyzs).transpose(2,1,0) xyzas = np.array(xyzas).transpose(2,1,0) def animate(n): for i in range(len(m)): xyz = xyzs[i] traces[i].set_data(xyz[0,:n],xyz[1,:n]) traces[i].set_3d_properties(xyz[2,:n]) pts[i].set_data(xyz[0,n],xyz[1,n]) pts[i].set_3d_properties(xyz[2,n]) for i in range(N_ast): pt_asts[i].set_data(xyzas[i,0,n],xyzas[i,1,n]) pt_asts[i].set_3d_properties(xyzas[i,2,n]) return traces+pts+pt_asts ani = animation.FuncAnimation(fig, animate, range(N), interval=10, blit=True) plt.show() ani.save(name)
总结
本篇文章就到这里了,希望能够给你带来帮助,也希望您能够多多关注我们的更多内容!
精彩评论