test.py

#ローパス関数
def low_path(xx):
	sample_rate = 100.0
	nsamples = 400
	t = arange(nsamples) / sample_rate
	#t = framerate
	x = xx

	nyq_rate = sample_rate / 2.0 #ナイキスト周波数
	width = 5.0/nyq_rate #正規化
	ripple_db = 60.0
	numtaps = 255#フィルタ係数（タップ）の数（要奇数）
	cutoff_hz = 10.0

	b = scipy.signal.firwin(numtaps, cutoff_hz/nyq_rate)
	filtered_x = scipy.signal.lfilter(b, 1.0, x)	
	return filtered_x

def band_path(xx):
	sample_rate = 100.0
	nsamples = 400
	t = arange(nsamples) / sample_rate
	#t = framerate
	x = xx

	nyq_rate = sample_rate / 2.0 #ナイキスト周波数
	width = 5.0/nyq_rate #正規化
	ripple_db = 60.0
	numtaps = 255#フィルタ係数（タップ）の数（要奇数）
	cutoff_hz = 10.0

	fe1 = 10.0/nyq_rate
	fe2 = 30.0/nyq_rate

	b = scipy.signal.firwin(numtaps, [fe1,fe2],pass_zero=False)
	filtered_x = scipy.signal.lfilter(b, 1.0, x)	
	return filtered_x

def high_path(xx):
	sample_rate = 100.0
	nsamples = 400
	t = arange(nsamples) / sample_rate
	#t = framerate
	x = xx

	nyq_rate = sample_rate / 2.0 #ナイキスト周波数
	width = 5.0/nyq_rate #正規化
	ripple_db = 60.0
	numtaps = 255#フィルタ係数（タップ）の数（要奇数）
	#cutoff_hz = 300.0

	#30*10^2[Hz]
	fe = 30.0/nyq_rate


	b = scipy.signal.firwin(numtaps, fe ,pass_zero=False)
	filtered_x = scipy.signal.lfilter(b, 1.0, x)	
	return filtered_x

def fft_proc(data,framerate,start,sample_num):
    #X= scipy.fftpack.fft(data[start:start+sample_num]) # fft
    X= np.fft.fft(data[start:start+sample_num]) # fft
    freqList = np.fft.fftfreq(sample_num, d=1.0/framerate)  # 周波数軸の値を計算
    amplitudeSpectrum = [np.sqrt(c.real ** 2 + c.imag ** 2) for c in X]  # 振幅スペクトル
    return freqList, amplitudeSpectrum

def read_wave(filename):
    wf=wave.open(filename,"r")
    framerate=wf.getframerate()# サンプリング周波数
    data=wf.readframes(wf.getnframes())
    data=frombuffer(data,dtype="int16")/32768.0 #正規化
    wf.close()
    return data, framerate