How Python uses matplotlib to draw animations

This example describes how Python uses matplotlib to draw animations. Share to everyone for your reference. The specific analysis is as follows:

Matplotlib starting from 1.1.0 to support drawing animations

Here are a few examples:

The first example uses generator, which runs the function Data_gen every two seconds:

#-*-Coding:utf-8-*-  import numpy as NP import Matplotlib.pyplot as PLT import matplotlib.animation as animation fi g = plt.figure () axes1 = Fig.add_subplot (111) Line, = Axes1.plot (Np.random.rand)) #因为update的参数是调用函数data_gen, # So the first default parameter cannot be framenum def update (data):   line.set_ydata (data)   return line, # 10 random Data def data_gen () generated each time:   While True:     yield Np.random.rand (ten) ANI = animation. Funcanimation (Fig, update, Data_gen, interval=2*1000) plt.show ()

The second example uses list (metric), each time a row of data from the metric is fed into the update as a parameter:

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  .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, the default is to fetch one element in the list each time, #即metric [0], METRIC[1],... def update (data):   line.set_ydata (data)   

A third example:

Import NumPy as NP from matplotlib import Pyplot as plt from matplotlib import Animation # First set up the figure, the ax is, 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 was called sequentially # note:i is Framenumber def animate (i):   x = Np.linspace (0, 2, +)   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 has changed. Anim = animation. Funcanimation (Fig, animate, Init_func=init,                 

A fourth example:

#-*-Coding:utf-8-*-import numpy as NP import Matplotlib.pyplot as PLT import matplotlib.animation as animation # each generation A new coordinate point def data_gen ():   t = data_gen.t   cnt = 0   while cnt <:     cnt+=1     T + = 0.05     yield T, NP.S In (2*np.pi*t) * NP.EXP (-T/10.) data_gen.t = 0 # drawing 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 = [], [] # because the parameter of run is called function data_gen,# so the first argument can be not framenum: Set line data, return to Line de F 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, # calls the function Run,run every 10 seconds for the function Data_gen, # indicates that the graph only updates the element that needs to be drawn, Ani = animation. Funcanimation (Fig, run, Data_gen, Blit=true, interval=10,   

Let's look at the following example:

#-*-Coding:utf-8-*-import numpy as NP import Matplotlib.pyplot as PLT import matplotlib.animation as animation #第一个参数 Must be Framenum def update_line (num, data, line):   line.set_data (Data[...,:num])   return line, FIG1 = Plt.figure () data = Np.random.rand (2, +) L, = Plt.plot ([], [], ' R ') Plt.xlim (0, 1) plt.ylim (0, 1) plt.xlabel (' x ') plt.title (' Test ') # Framenum increased from 1 to 25, returning again from 1 to 25, then returning ... 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 will increase from 11 to know Infinity #由于frame达到25以后, the data no longer change, so you will find that after reaching 25, the graph no longer changes #line_ani = animation. Funcanimation (FIG1, Update_line, fargs= (data, L), #  

Hopefully this article will help you with Python programming.

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