def show_wav():
wave = thinkdsp.read_wave(sys.argv[1])
#wave.normalize() # 归一化
#wave.apodize() # 渐入渐出
#segment = wave.segment(start=0, duration=2/440)
#segment.plot()
wave.plot()
plt.show()
# 频谱
spectrum = wave.make_spectrum()
spectrum.plot()
plt.show()
def plot(self, frame_rate=11025):
duration = self.period * 3
wave = self.make_wave(duration, start=0, frame_rate=frame_rate)
wave.plot()
def plot(self, framerate=11025):
duration = self.period() * 3
wave = self.make_wave(duration, start=0, framerate=framerate)
wave.plot()
PI2 = 2 * np.pi
class SawtoothChirp(Chirp):
def evaluate(self, ts):
freqs = np.linspace(self.start, self.end, len(ts))
dts = np.diff(ts, prepend=0)
dphis = PI2 * freqs * dts
phases = np.cumsum(dphis)
cycles = phases / PI2
frac, _ = np.modf(cycles)
ys = normalize(unbias(frac), self.amp)
return ys
signal = SawtoothChirp(start=220, end=880)
wave = signal.make_wave(duration=0.1, framerate=4000)
wave.apodize()
wave.write(filename="output3-2.wav")
plt.subplot(1, 2, 1)
plt.title("SawtoothChirp")
wave.plot()
sp = wave.make_spectrum(256)
plt.subplot(1, 2, 2)
sp.plot()
plt.xlabel("时间")
plt.ylabel("频率")
plt.title("频谱")
plt.show()
def noiseRemoval():
data = wave.load('A00269')
wave.plot(data, title="A00269")
data = wave.discardNoise(data)
wave.plot(data, title="A00269 - After noise removal")
level = 6
omission = ([1,2], True) # 5-40 hz
rebuilt = wave.decomp(data, 'sym5', level, omissions=omission)
wave.plot(rebuilt, title="A00269 - After wavelet decompisition")
data = wave.load('A00420')
wave.plot(data, title="A00420")
data = wave.discardNoise(data)
wave.plot(data, title="A00420 - After noise removal")
rebuilt = wave.decomp(data, 'sym5', level, omissions=omission)
wave.plot(rebuilt, title="A00420 - After wavelet decompisition")
data = wave.load('A00550')
wave.plot(data, title="A00550")
data = wave.discardNoise(data)
wave.plot(data, title="A00550 - After noise removal")
rebuilt = wave.decomp(data, 'sym5', level, omissions=omission)
wave.plot(rebuilt, title="A00420 - After wavelet decompisition")
#x=0
#for i in range(0, len(records)):
# print('working record:' + records[i])
# x+=1
# data = wave.load(records[i])
# sig = Signal(records[i],data)
#
# RR_interval = wave.RR_interval(sig.RPeaks)
#
# RR_interval_diff = wave.interval(RR_interval)
#
# bin_RR_intervals = wave.RR_interval_bin(RR_interval)
# print (bin_RR_intervals)
"""
# Testing QS points
data = wave.load('A00857')
wave.plot(data)
signal = Signal('A00857', data)
signal.plotRPeaks()
fig = plt.figure(figsize=(60, 6))
ax = fig.add_subplot(111)
ax.plot(signal.data)
ax.set_xlim(0, signal.data.size)
ax.plot(*zip(*signal.QSPoints), marker='o', color='r', ls='')
fig.savefig('/Users/samy/Downloads/graph.png')
plt.close()
"""