Pythonでフィルタリングツール

昨日の続き。
Python&matplotlibで移動平均フィルタリングアプリを作ってみた。
…とは言っても、かなりやっつけ仕事。

一応形にはなったので、画像とソースを張っておく。



左側がフィルタリング前の波形、右側がフィルタリング後の波形。
左下のスライダーがノイズ成分の強度調整、右下のスライダーが移動平均フィルタの強度調整。


以下が、ソースコード。

#coding:utf-8

from pylab import *
from matplotlib.widgets import Slider, Button

#FIR filter
def FIR(array,FIRCoefficient):
    output = []

    for i in range(len(array)):
        temp = 0
        for j in range(len(FIRCoefficient)):
            temp += array[i - j] * FIRCoefficient[j]
        output.append(temp)
        
    return output

#Time axis
t = arange(0.0,1.0,0.0001)
f = 10
s = []

#Noise cofficient
nc = 1

#Noisy sine wave
for i in range(len(t)):
    s.append(sin(2 * pi * f * t[i]) + nc * randn())
    
ax = subplot(121)
l, = plot(t,s)
axis([0,1,-10,10])
subplots_adjust(left=0.25, bottom=0.25)
xlabel("time(s)")
ax.set_position([0.1,0.5,0.35,0.3],"original")


#Filtered wave
FIRCoefficient = []
FIRlength = 10
for i in range(FIRlength):
    FIRCoefficient.append(1/ float(FIRlength))
s2 = FIR(s,FIRCoefficient)
ax2 = subplot(122)
m, = plot(t[:len(s2)],s2)
axis([0,1,-10,10])
ax2.set_position([0.55,0.5,0.35,0.3],"original")


#Noise controll
axcolor = 'lightgoldenrodyellow'
axnoise = axes([0.1,0.3,0.32,0.03], axisbg = axcolor)
snoise = Slider(axnoise,"Noise",0.0,10.0,valinit = 1)

def update(val):
    global s
    nc = snoise.val
    s = []
    for i in range(len(t)):
        s.append(sin(2 * pi * f * t[i]) + nc * randn())
    s = array(s)
    l.set_ydata(s)
    FIRCoefficient = []
    for i in range(FIRlength):
        FIRCoefficient.append(1/ float(FIRlength))
    s2 = FIR(s,FIRCoefficient)
    m.set_ydata(s2)
    draw()
snoise.on_changed(update)


#Filter length controll
axfilter = axes([0.55,0.3,0.32,0.03], axisbg = axcolor)
sfilter = Slider(axfilter,"Filter",5,30,valinit = 10)

def filtering(val):
    global FIRlength
    FIRlength = int(sfilter.val)
    FIRCoefficient = []
    #Moving average filter
    for i in range(FIRlength):
        FIRCoefficient.append(1/ float(FIRlength))
    s2 = FIR(s,FIRCoefficient)
    m.set_ydata(s2)
    draw()
sfilter.on_changed(filtering)

show()

昨日作ったアプリと早いところ統合したいなぁ。
でも、その前にどっちのアプリも個別にブラッシュアップしとかないと。