Python 低通滤波器

Python低通滤波器

读取ExcelProc目录下的out.txt文件中的波形数据，然后绘制出原始数据波形，最后再通过低通滤波器进行一次滤波

# -*- coding: utf-8 -*-


from scipy import signal
import numpy as np
import matplotlib.pyplot as pl
import matplotlib
import math

N = 0#500
fs = 5
n = []#[2*math.pi*fs*t/N for t in range(N)]
n1 = [2*math.pi*fs*t/N for t in range(N)]
fileObj = open("ExcelProc\out.txt",'r')
for line in fileObj.readlines():    #依次读取每行
    FuelVol = line#.split() #根据空格提取每个内容
    FuelVol = int(FuelVol) 
    n.append(FuelVol)<span style="white-space:pre">	</span>#将波形数据值依次添加到序列n中
    N += 1
    
while N%12 != 0:
    n.append(int(0))
    N += 1
print("N is deal ",N)
axis_x = np.linspace(0,1,num=N)
#设置字体文件，否则不能显示中文
#myfont = matplotlib.font_manager.FontProperties(fname='c:\\windows\\fonts\\fzshjw_0.ttf')

#频率为5Hz的正弦信号
#x = [math.sin(i) for i in n]
x = n
pl.subplot(221)
pl.plot(axis_x,x)
pl.title(u'5Hz Sin')
pl.axis('tight')


b,a = signal.butter(3,0.15,'low')
sf = signal.filtfilt(b,a,x)

pl.subplot(222)
pl.plot(axis_x,sf)
pl.title(u'Low Pass')
pl.axis('tight')
fileout = open("Out.txt","w")
fileout.write("const unsigned int datas[]={")
line = 0
for i in sf:
    i = int(i)
    if(line%36 == 0):
        fileout.write("\n")
    fileout.write(str(i)+",")
    line += 1
fileout.write("};")
fileout.close()
pl.show()

# -*- coding: utf-8 -*-


from scipy import signal
import numpy as np
import matplotlib.pyplot as pl
import matplotlib
import math

N = 0#500
fs = 5
n = []#[2*math.pi*fs*t/N for t in range(N)]
n1 = [2*math.pi*fs*t/N for t in range(N)]
fileObj = open("ExcelProc\out.txt",'r')
for line in fileObj.readlines():    #依次读取每行
    FuelVol = line#.split() #根据空格提取每个内容
    FuelVol = int(FuelVol)
    n.append(FuelVol)
    N += 1
    
while N%12 != 0:
    n.append(int(0))
    N += 1
print("N is deal ",N)
axis_x = np.linspace(0,1,num=N)
#设置字体文件，否则不能显示中文
#myfont = matplotlib.font_manager.FontProperties(fname='c:\\windows\\fonts\\fzshjw_0.ttf')

#频率为5Hz的正弦信号
#x = [math.sin(i) for i in n]
x = n
pl.subplot(231)
pl.plot(axis_x,x)
pl.title(u'5Hz Sin')
pl.axis('tight')

x1 = []
length = (len(x)*5/7)
x1 = x[-length:]

pl.subplot(232)
axis_x1 = np.linspace(0,1,num=len(x1))
pl.plot(axis_x1,x1)
pl.title(u'ps')
pl.axis('tight')

x2 = x[:len(x)-length]
pl.subplot(233)
axis_x1 = np.linspace(0,1,num=len(x2))
pl.plot(axis_x1,x2)
pl.title(u'pd')
pl.axis('tight')


b,a = signal.butter(3,0.13,'low')
sf = signal.filtfilt(b,a,x1)

pl.subplot(234)
axis_x1 = np.linspace(0,1,num=len(x1))
pl.plot(axis_x1,sf)
pl.title(u'Low Pass')
pl.axis('tight')
fileout = open("Out.txt","w")
fileout.write("const unsigned int data[]@0xC000={")
line = 0
outx = []
outx = x2
for i in sf:
    outx.append(i)
    
pl.subplot(235)
axis_x1 = np.linspace(0,1,num=len(outx))
pl.plot(axis_x1,outx)
pl.title(u'Low Pass')
pl.axis('tight')

sampling_rate = 8000
fft_size = len(outx)
xf = np.fft.rfft(outx)/fft_size
freqs = np.linspace(0, sampling_rate/2, fft_size/2+1)
xfp = 20*np.log10(np.clip(np.abs(xf), 1e-20, 1e100))
pl.subplot(236)
pl.plot(freqs, xfp)
pl.xlabel(u"Freq(Hz)")
pl.subplots_adjust(hspace=0.4)

for i in outx:
    i = int(i)
    if(line%36 == 0):
        fileout.write("\n")
    fileout.write(str(i)+",")
    line += 1
fileout.write("};")
fileout.close()
pl.show()