import numpy as np import matplotlib.pyplot as plt from matplotlib.pyplot import MultipleLocator import csv from scipy import signal#去線性趨勢主要用的庫 import numpy as npdata = [] data1 = [] data2 = [] data3 = [] # with open('D:\keyan_z\lvbo_output\lvbo.csv','r') as csvfile: with open('C://Users//Lenovo//Desktop//999.csv', 'r') as csvfile:reader = csv.reader(csvfile)for row in reader:data.append(float(row[0]))data1.append(float(row[1]))#原數(shù)據(jù)data2.append(float(row[2]))#原數(shù)據(jù)data3.append(float(row[3]))#原數(shù)據(jù) # print(numpy.array(data)) a_detrend=signal.detrend(data1, axis=0, type='linear')#去線性趨勢后的數(shù)據(jù) b_detrend=signal.detrend(data2, axis=0, type='linear')#去線性趨勢后的數(shù)據(jù) c_detrend=signal.detrend(data3, axis=0, type='linear')#去線性趨勢后的數(shù)據(jù) # plt.plot(data1, color='lightcoral') # plt.plot(a_detrend+np.array(data1).mean())plt.plot(data2, color='orange') plt.plot(b_detrend)#只對(duì)比 # plt.plot(data3, color='cornflowerblue')# plt.title('model loss and acc') plt.ylabel('gait') plt.xlabel('Time(0.01s)') plt.legend(['raw-data', 'detrend'],loc='upper right') plt.show()# # print(data2) # plt.subplot(4, 1, 1) # plt.plot(data) # plt.ylabel('raw') # # plt.xlabel('Time(0.01s)') # # x_major_locator = MultipleLocator(10) # # y_major_locator = MultipleLocator(0.2)# 把y軸的刻度間隔設(shè)置為0.1，并存在變量里 # # ax = plt.gca()# ax為兩條坐標(biāo)軸的實(shí)例 # # ax.xaxis.set_major_locator(x_major_locator) # # ax.yaxis.set_major_locator(y_major_locator)# 把y軸的主刻度設(shè)置為0.1的倍數(shù) # # plt.xlim(1, 100) # # plt.ylim(0.8, 1.4)# 把y軸的刻度范圍設(shè)置為-5到110，同理，-5不會(huì)標(biāo)出來，但是能看到一點(diǎn)空白 # # plt.subplot(4, 1, 2) # plt.plot(data1) # plt.ylabel('butterwolth') # # plt.subplot(4, 1, 3) # plt.plot(data2) # plt.ylabel('sliding') # # plt.subplot(4, 1, 4) # plt.plot(data3) # plt.ylabel('low') # plt.xlabel('Sample point') # # # # plt.legend() # plt.show() # # # #

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