importnumpyasnpimportmatplotlib.pyplotaspltfrommatplotlib.animationimportFuncAnimation#导入负责绘制动画的接口#其中需要输入一个更新数据的函数来为fig提供新的绘图信息fig, ax = plt.subplots()#生成轴和fig, 可迭代的对象x, y= [], []#用于接受后更新的数据line, = plt.plot([], [],'.-')#绘制线对象,...
line,=plt.plot(x,y) # 动画函数 def animate(i): line.set_ydata(np.sin(x+i/10)) return line, # 动画初始化函数 def init(): line.set_ydata(np.sin(x)) return line, animation.FuncAnimation(fig=fig,func=animate,frames=100,init_func=init,interval=20,blit=True) plt.show() 1. 2. ...
下面是一个很基本的例子: """A simple example of an animated plot"""importnumpy as npfrommatplotlibimportpyplot as pltfrommatplotlibimportanimation#First set up the figure, the axis, and the plot element we want to animatefig =plt.figure()#create our line object which will be modified in th...
In our first static line plot, we started the plot at this point, but for the animated line plot, we need tobuild the plot in a function. At a minimum, the function that builds the plot needs to accept one argument that corresponds to the frame number in the animation. This frame num...
画这类图的关键是要给出不断更新的函数,这里就是update函数了。注意,line, = ax.plot([], [], 'r-', animated=False)中的,表示创建tuple类型。迭代更新的数据frame取值从frames取得。 例子2. 动态显示一个动点,它的轨迹是sin函数。 import numpy as np ...
ax.plot(x,y) ax.plot(x,x**3) print(ax.lines); # 通过直接使用辅助方法画线,打印ax.lines后可以看到在matplotlib在底层创建了两个Line2D对象 代码2: fig,ax= plt.subplots() lines = [Line2D(x, y), Line2D(x, x**3,color='orange')] # 显式创建Line2D对象 ...
"""def__init__(self,ax,plot_type="line",string="Frame: {:.2f}",**kwargs):self.__ax=...
line, =plt.plot(x, y, '-')line.set_antialiased(False)# 关闭抗锯齿 使用setp函数 setp 函数...
>>> plt.setp(line) agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array alpha: scalar or None animated: bool antialiased or aa: bool clip_box: `.Bbox`
当你调用Axes的绘图方法(例如plot),它将创建一组Line2D对象,并将所有的关键字参数传递给这些Line2D对象,并将它们添加进Axes.lines属性中,最后返回所创建的Line2D对象列表: x1 = np.linspace(0.0, 5.0) x2 = np.linspace(0.0, 3.0) y1 = np.cos(2 * np.pi * x1) * np.exp(-x1) ...