具有多个粒子的FuncAnimation

Question

下面是一个我已经工作了几个星期的模型，随着我学习如何编码（给新手编码），慢慢地增加了更多的复杂性。如果不清楚的话，我试图建立一个由两种不同密度的粒子组成的模型，它们根据斯托克斯沉降速度（作为浓度的函数）沉降。我有麻烦让动画与第二个粒子（工作代码与一个动画粒子在底部）。为了调试代码，我分解了两个不同粒子的变量，但没有运气确定我做错了什么。在

任何帮助将不胜感激！在

import numpy as np
import matplotlib.pyplot as plt
from pylab import *
from matplotlib.animation import FuncAnimation
import random
import pdb
from scipy import spatial
from scipy.spatial import KDTree

n = 100
n2 = 50
sigma = 0.01
sigma2 = 0.01

pp = 2.56 # pp = particle density (Sphene=3.53) #(Feldspar=2.56) 
#(g/cm^3)

pp2 = 3.53

pf = 2.7 # pf = fluid density(g/cm^3)

pf2 = 2.7

g = 9.8 # g = gravity (m/s^2)

g2 = 9.8

r = 0.003 # r = radius of sphere (meter)

r2 = 0.0002

mu = 0.53 # mu = dynamic viscosity of fluid (log10Poise)

mu2 = 0.53

rp = 0.01 #radius around particle to check for nearest neighbor

rp2 = 0.001

dt = 0.008

dt2 = 0.008

fig, ax = plt.subplots()

az = plt.axes(xlim=(-.5, .5), ylim=(-1, 0))

xdata, ydata = [0.0], [0.0]

xdata2, ydata2 = [0.0], [0.0]

ln, = plt.plot([], [], marker= 'o', 
markerfacecolor='r',markeredgecolor='k', linestyle='None', 
animated=True)

ln2, = plt.plot([], [], marker= 's', 
markerfacecolor='b',markeredgecolor='k', linestyle='None', 
animated=True)

#pdb.set_trace()
def v_stokes(pp,pf,g,r,mu):
    top=2*(pp-pf)*g*(r**2)
    bottom=9*mu
    ws=top/bottom
    return ws

def v_stokes2(pp2,pf2,g2,r2,mu2):
    top2=2*(pp2-pf2)*g2*(r2**2)
    bottom2=9*mu2
    ws2=top2/bottom2
    return ws2


def init():
    ax.set_xlim(  -2, 2)
    ax.set_ylim(-10, 0)
    return ln, ln2,

def concentration(xdata, ydata, rp):
    coords = list(zip(xdata, ydata))
    tree = spatial.KDTree(coords)
    test = np.column_stack([xdata, ydata])
    nnl = tree.query_ball_point(test, rp) #nearest neighbors as a list 
    #(had tree in here before test but shape was wrong)
    #pdb.set.trace()
    nnt = np.zeros(len(nnl)) #nearest neighbors total
    for i in range(len(nnt)): 
        nnt[i] = len(nnl[i])
    return nnt

def concentration2(xdata2, ydata2, rp2):
    coords2 = list(zip(xdata2, ydata2))
    tree2 = spatial.KDTree(coords2)
    test2 = np.column_stack([xdata2, ydata2])
    nnl2 = tree2.query_ball_point(test2, rp2)  
    nnt2 = np.zeros(len(nnl2)) #nearest neighbors total
    for i in range(len(nnt2)): 
        nnt2[i] = len(nnl2[i])
    return nnt2

#y0 = []
#y1 = []
#y2 = []
#y3 = []
#y4 = []
def update(frame):

    global xdata
    global ydata
    global concentration, v_stokes, pp, pf, g, r, mu, rp, dt, n, sigma

    xdata = xdata + np.random.normal(0, sigma, n)

    wss = v_stokes(pp,pf,g,r,mu)

    if frame == 0.0:
        ydata = np.zeros(len(xdata)) #makes the ydata length = xdata at 
        #time 0 print(ydata)
        rp = 0.003

    if frame > 10:
        rp = 0.008

    cp = concentration(xdata, ydata, rp)
    if np.any(cp == 1):
        cp = cp-1

    if frame > 0.0:
        #y0.append(ydata)
        #y1.append(wss)
        #y2.append(cp)
        #y3.append(dt)
        #y4.append(xdata)
        ydata = ydata + (wss*(1-cp)**3) - dt # [0] 
        for v in ydata:
            if v < -1.001:
                ydata = -1
    ln.set_data(xdata, ydata)
    return ln,


def update2(frame2):

    global xdata2
    global ydata2
    global concentration2, v_stokes2, pp2, pf2, g2, r2, mu2, rp2, dt2, 
    n2, sigma2

    xdata2 = xdata2 + np.random.normal(0, sigma2, n2)

    wss2 = v_stokes2(pp2,pf2,g2,r2,mu2)

    if frame2 == 0.0:
        ydata2 = np.zeros(len(xdata2)) #makes the ydata length = xdata 
        #at time 0 print(ydata)
        rp2 = 0.003

    if frame2 > 10:
        rp2 = 0.008

    cp2 = concentration2(xdata2, ydata2, rp2)
    if np.any(cp2 == 1):
        cp2 = cp2-1

    if frame2 > 0.0:
        #y5.append(ydata2)
        #y6.append(wss2)
        #y7.append(cp2)
        #y8.append(dt2)
        #y9.append(xdata2)

        ydata2 = ydata2 + (wss2*(1-cp2)**3) - dt2 # [0] 
        for v2 in ydata2:
            if v2 < -1.001:
                ydata2 = -1

     ln2.set_data(xdata2, ydata2)
     return ln2,

def update_all(i):
    l1 = update(i)
    l2 = update2(i)
    return l1, l2,

ani = FuncAnimation(fig, update_all, frames=range(0,200),
                    init_func=init, blit=True, interval=100, repeat = 
False)
# change frames=range(0:1000) to change the number of frames 

plt.show()

下面是一个动画粒子的原始工作代码：

^{pr2}$

Answer 1

^{}期望第二个参数是一个可调用的（例如函数）来更新绘图。在

func : callable
The function to call at each frame. The first argument will be the next value in frames. Any additional positional arguments can be supplied via the fargs parameter.

如果要更新两个函数，则需要将它们合并为一个函数

def update_all(i):
    l1 = update(i)
    l2 = update2(i)
    return l1,l2

ani = FuncAnimation(fig, update_all, frames=range(0,200), init_func=init, ...)

请注意，您需要以与通常相同的方式定义plot，并且需要在两个更新函数中返回line对象本身。在

完整运行代码：

和13；