python處理csv資料動態顯示曲線執行個體代碼,pythoncsv

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python處理csv資料動態顯示曲線執行個體代碼,pythoncsv

本文研究的主要是python處理csv資料動態顯示曲線,分享了實現代碼,具體如下。

代碼:

# -*- coding: utf-8 -*- """ Spyder Editor  This temporary script file is located here: C:\Users\user\.spyder2\.temp.py """ """ Show how to modify the coordinate formatter to report the image "z" value of the nearest pixel given x and y """ # coding: utf-8  import time import string import os  import math  import pylab  import numpy as np from numpy import genfromtxt import matplotlib import matplotlib as mpl from matplotlib.colors import LogNorm from matplotlib.mlab import bivariate_normal  import matplotlib.pyplot as plt import matplotlib.cm as cm   import matplotlib.animation as animation        metric = genfromtxt('D:\export.csv', delimiter=',')  lines=len(metric)  #print len(metric) #print len(metric[4]) #print metric[4]   rowdatas=metric[:,0] for index in range(len(metric[4])-1):   a=metric[:,index+1]   rowdatas=np.row_stack((rowdatas,a))    #print len(rowdatas) #print len(rowdatas[4]) #print rowdatas[4]  #    #plt.figure(figsize=(38,38), dpi=80) #plt.plot(rowdatas[4] ) #plt.xlabel('time') #plt.ylabel('value') #plt.title("USBHID data analysis") #plt.show()  linenum=1 ##如果是參數是list,則預設每次取list中的一個元素,即metric[0],metric[1],...  listdata=rowdatas.tolist() print listdata[4]  #fig = plt.figure()  #window = fig.add_subplot(111)  #line, = window.plot(listdata[4] )    fig, ax = plt.subplots() line, = ax.plot(listdata[4],lw=2) ax.grid()  time_template = 'Data ROW = %d' time_text = ax.text(0.05, 0.9, '', transform=ax.transAxes)   #ax = plt.axes(xlim=(0, 700), ylim=(0, 255))  #line, = ax.plot([], [], lw=2)    def update(data):    global linenum   line.set_ydata(data) #  print 'this is line: %d'%linenum   time_text.set_text(time_template % (linenum))   linenum=linenum+1 #  nextitem = input(u'輸入任一字元繼續: ')   return line,   def init(): #  ax.set_ylim(0, 1.1) #  ax.set_xlim(0, 10) #  line.set_data(xdata)   plt.xlabel('time')   plt.ylabel('Time')   plt.title('USBHID Data analysis')   return line,    ani = animation.FuncAnimation(fig, update,listdata , interval=1*1000,init_func=init,repeat=False)  plt.show()  

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