matplotlib绘制动画的示例

matplotlib从1.1.0版本以后就开始支持绘制动画

下面是几个的示例：

第一个例子使用generator，每隔两秒，就运行函数data_gen：

# -*- coding: utf-8 -*- import numpy as npimport matplotlib.pyplot as pltimport matplotlib.animation as animationfig = plt.figure()axes1 = fig.add_subplot(111)line, = axes1.plot(np.random.rand(10))#因为update的参数是调用函数data_gen,所以第一个默认参数不能是framenumdef update(data):    line.set_ydata(data)    return line,# 每次生成10个随机数据def data_gen():    while True:        yield np.random.rand(10)ani = animation.FuncAnimation(fig, update, data_gen, interval=2*1000)plt.show()

第二个例子使用list（metric），每次从metric中取一行数据作为参数送入update中：

import numpy as npimport matplotlib.pyplot as pltimport matplotlib.animation as animationstart = [1, 0.18, 0.63, 0.29, 0.03, 0.24, 0.86, 0.07, 0.58, 0]metric =[[0.03, 0.86, 0.65, 0.34, 0.34, 0.02, 0.22, 0.74, 0.66, 0.65],         [0.43, 0.18, 0.63, 0.29, 0.03, 0.24, 0.86, 0.07, 0.58, 0.55],         [0.66, 0.75, 0.01, 0.94, 0.72, 0.77, 0.20, 0.66, 0.81, 0.52]        ]fig = plt.figure()window = fig.add_subplot(111)line, = window.plot(start)#如果是参数是list,则默认每次取list中的一个元素,即metric[0],metric[1],...def update(data):    line.set_ydata(data)    return line,ani = animation.FuncAnimation(fig, update, metric, interval=2*1000)plt.show()

第三个例子：

import numpy as npfrom matplotlib import pyplot as pltfrom matplotlib import animation# First set up the figure, the axis, and the plot element we want to animatefig = plt.figure()ax = plt.axes(xlim=(0, 2), ylim=(-2, 2))line, = ax.plot([], [], lw=2)# initialization function: plot the background of each framedef init():    line.set_data([], [])    return line,# animation function.  This is called sequentially# note: i is framenumberdef animate(i):    x = np.linspace(0, 2, 1000)    y = np.sin(2 * np.pi * (x - 0.01 * i))    line.set_data(x, y)    return line,# call the animator.  blit=True means only re-draw the parts that have changed.anim = animation.FuncAnimation(fig, animate, init_func=init,                               frames=200, interval=20, blit=True)#anim.save('basic_animation.mp4', fps=30, extra_args=['-vcodec', 'libx264'])plt.show()

第四个例子:

# -*- coding: utf-8 -*- import numpy as npimport matplotlib.pyplot as pltimport matplotlib.animation as animation# 每次产生一个新的坐标点def data_gen():    t = data_gen.t    cnt = 0    while cnt < 1000:        cnt+=1        t += 0.05        yield t, np.sin(2*np.pi*t) * np.exp(-t/10.)data_gen.t = 0# 绘图fig, ax = plt.subplots()line, = ax.plot([], [], lw=2)ax.set_ylim(-1.1, 1.1)ax.set_xlim(0, 5)ax.grid()xdata, ydata = [], []# 因为run的参数是调用函数data_gen,所以第一个参数可以不是framenum:设置line的数据,返回linedef run(data):    # update the data    t,y = data    xdata.append(t)    ydata.append(y)    xmin, xmax = ax.get_xlim()    if t >= xmax:        ax.set_xlim(xmin, 2*xmax)        ax.figure.canvas.draw()    line.set_data(xdata, ydata)    return line,    # 每隔10秒调用函数run,run的参数为函数data_gen,# 表示图形只更新需要绘制的元素ani = animation.FuncAnimation(fig, run, data_gen, blit=True, interval=10,    repeat=False)plt.show()

再看下面的例子:

# -*- coding: utf-8 -*-import numpy as npimport matplotlib.pyplot as pltimport matplotlib.animation as animation#第一个参数必须为framenumdef update_line(num, data, line):    line.set_data(data[...,:num])    return line,fig1 = plt.figure()data = np.random.rand(2, 15)l, = plt.plot([], [], 'r-')plt.xlim(0, 1)plt.ylim(0, 1)plt.xlabel('x')plt.title('test')#framenum从1增加大25后,返回再次从1增加到25,再返回...line_ani = animation.FuncAnimation(fig1, update_line, 25,fargs=(data, l),interval=50, blit=True)#等同于#line_ani = animation.FuncAnimation(fig1, update_line, frames=25,fargs=(data, l),#    interval=50, blit=True)#忽略frames参数,framenum会从1一直增加下去知道无穷#由于frame达到25以后,数据不再改变,所以你会发现到达25以后图形不再变化了#line_ani = animation.FuncAnimation(fig1, update_line, fargs=(data, l),#    interval=50, blit=True)plt.show()