I am trying to make an animation of the double pendulum using the
attached script (v1.1.x branch). It creates all the files _tmp*.png,
and creates the mpg but it has zero file size. If I manually make the
movie with the resultant PNGs, it works fine
mencoder mf://_tmp*.png -mf type=png:fps=15 -ovc lavc -lavcopts
vcodec=mpeg4 -oac copy -o test2.mpg
I need to add some debugging output to animation.py (we should add
lots of verbose.report command in there to see what is going on, I'm
going to try and get a pull request together) but I thought I'd fire
this off to anyone else has the same problems or if I'm doing it
wrong. I do have ffmpeg and mencoder installed on my 64bit ubuntu
11.04 box.
Thanks,
JDH
# Double pendulum formula translated from the C code at
# http://www.physics.usyd.edu.au/~wheat/dpend_html/solve_dpend.c
from numpy import sin, cos, pi, array
import numpy as np
import matplotlib.pyplot as plt
import scipy.integrate as integrate
import matplotlib.animation as animation
G = 9.8 # acceleration due to gravity, in m/s^2
L1 = 1.0 # length of pendulum 1 in m
L2 = 1.0 # length of pendulum 2 in m
M1 = 1.0 # mass of pendulum 1 in kg
M2 = 1.0 # mass of pendulum 2 in kg
def derivs(state, t):
dydx = np.zeros_like(state)
dydx[0] = state[1]
del_ = state[2]-state[0]
den1 = (M1+M2)*L1 - M2*L1*cos(del_)*cos(del_)
dydx[1] = (M2*L1*state[1]*state[1]*sin(del_)*cos(del_)
+ M2*G*sin(state[2])*cos(del_) + M2*L2*state[3]*state[3]*sin(del_)
- (M1+M2)*G*sin(state[0]))/den1
dydx[2] = state[3]
den2 = (L2/L1)*den1
dydx[3] = (-M2*L2*state[3]*state[3]*sin(del_)*cos(del_)
+ (M1+M2)*G*sin(state[0])*cos(del_)
- (M1+M2)*L1*state[1]*state[1]*sin(del_)
- (M1+M2)*G*sin(state[2]))/den2
return dydx
# create a time array from 0..100 sampled at 0.1 second steps
dt = 0.05
t = np.arange(0.0, 20, dt)
# th1 and th2 are the initial angles (degrees)
# w10 and w20 are the initial angular velocities (degrees per second)
th1 = 120.0
w1 = 0.0
th2 = -10.0
w2 = 0.0
rad = pi/180
# initial state
state = np.array([th1, w1, th2, w2])*pi/180.
# integrate your ODE using scipy.integrate.
y = integrate.odeint(derivs, state, t)
x1 = L1*sin(y[:,0])
y1 = -L1*cos(y[:,0])
x2 = L2*sin(y[:,2]) + x1
y2 = -L2*cos(y[:,2]) + y1
fig = plt.figure()
ax = fig.add_subplot(111, autoscale_on=False, xlim=(-2, 2), ylim=(-2, 2))
ax.grid()
line, = ax.plot([], [], 'o-', lw=2)
time_template = 'time = %.1fs'
time_text = ax.text(0.05, 0.9, '', transform=ax.transAxes)
def init():
line.set_data([], [])
time_text.set_text('')
return line, time_text
def animate(i):
thisx = [0, x1[i], x2[i]]
thisy = [0, y1[i], y2[i]]
line.set_data(thisx, thisy)
time_text.set_text(time_template%(i*dt))
return line, time_text
ani = animation.FuncAnimation(fig, animate, np.arange(1, len(y)),
interval=25, blit=True, init_func=init)
ani.save('jdh.mpg', fps=15, clear_temp=False)
plt.show()
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