Python使用matplotlib绘制动画的方法

本文实例讲述了Python使用matplotlib绘制动画的方法。分享给大家供大家参考。具体分析如下：

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() 

希望本文所述对大家的python程序设计有所帮助。