matplotlib绘制动画代码示例_Python

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 np 

									import matplotlib.pyplot as plt 

									import matplotlib.animation as animation 

									fig = 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framenum 

									def 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 np 

									import matplotlib.pyplot as plt 

									import matplotlib.animation as animation 

									start = [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 np 

									from matplotlib import pyplot as plt 

									from matplotlib import animation 

									# First set up the figure, the axis, and the plot element we want to animate 

									fig = plt.figure() 

									ax = plt.axes(xlim=(0, 2), ylim=(-2, 2)) 

									line, = ax.plot([], [], lw=2) 

									# initialization function: plot the background of each frame 

									def init(): 

									  line.set_data([], []) 

									  return line, 

									# animation function. This is called sequentially 

									# note: i is framenumber 

									def 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 np 

									import matplotlib.pyplot as plt 

									import 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line 

									def 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 np 

									import matplotlib.pyplot as plt 

									import matplotlib.animation as animation 

									#第一个参数必须为framenum 

									def 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()