def plot_convolution():
response = thinkdsp.read_wave('180961__kleeb__gunshots.wav')
response = response.segment(start=0.26, duration=5.0)
response.normalize()
dt = 1
shift = dt * response.framerate
factor = 0.5
gun2 = response + shifted_scaled(response, shift, factor)
gun2.plot()
thinkplot.config(xlabel='time (s)',
ylabel='amplitude',
ylim=[-1.05, 1.05],
legend=False)
thinkplot.save(root='systems8')
signal = thinkdsp.SawtoothSignal(freq=410)
wave = signal.make_wave(duration=0.1, framerate=response.framerate)
total = 0
for j, y in enumerate(wave.ys):
total += shifted_scaled(response, j, y)
total.normalize()
wave.make_spectrum().plot(high=500, color='0.7', label='original')
segment = total.segment(duration=0.2)
segment.make_spectrum().plot(high=1000, label='convolved')
thinkplot.config(xlabel='frequency (Hz)', ylabel='amplitude')
thinkplot.save(root='systems9')
def view_harmonics(freq, framerate):
signal = thinkdsp.SawtoothSignal(freq)
wave = signal.make_wave(duration=0.5, framerate=framerate)
spectrum = wave.make_spectrum()
spectrum.plot(color='blue')
thinkplot.show(xlabel='frequency', ylabel='amplitude')
display(wave.make_audio())
def get_sawtooth_wave_data(freq,
offset,
duration=0.1,
framerate=40000,
noise_ratio=0):
signal = thinkdsp.SawtoothSignal(freq=freq, amp=1.0, offset=offset)
wave = signal.make_wave(duration=duration, start=0, framerate=framerate)
if noise_ratio != 0:
wave.ys += numpy.random.standard_normal(wave.ys.shape) * noise_ratio
return wave.ys
def get_sawtooth_square_wave(freq, offset, duration=0.1, framerate=40000):
signal_sawtooth = thinkdsp.SawtoothSignal(freq=freq,
amp=1.0,
offset=offset)
signal_square = thinkdsp.SquareSignal(freq=freq,
amp=1.0,
offset=offset + 2 * numpy.pi * 0.2)
components = [signal_sawtooth, signal_square]
signal = thinkdsp.SumSignal(*components)
wave = signal.make_wave(duration=duration, start=0, framerate=40000)
wave.ys = wave.ys / len(components) # normalization
return wave.ys
def plot_sawtooth(response):
signal = thinkdsp.SawtoothSignal(freq=441)
wave = signal.make_wave(duration=0.1, framerate=response.framerate)
total = 0
for t, y in zip(wave.ts, wave.ys):
total += shifted_scaled(response, t, y)
total.normalize()
high = 5000
wave.make_spectrum().plot(high=high, color='0.7', label='original')
segment = total.segment(duration=0.2)
segment.make_spectrum().plot(high=high, label='convolved')
thinkplot.config(xlabel='Frequency (Hz)', ylabel='Amplitude')
thinkplot.save(root='systems9')
def make_figures():
"""Makes figures showing complex signals.
"""
amps = numpy.array([0.6, 0.25, 0.1, 0.05])
freqs = [100, 200, 300, 400]
framerate = 11025
ts = numpy.linspace(0, 1, framerate)
ys = synthesize1(amps, freqs, ts)
print(ys)
thinkplot.preplot(2)
n = framerate / 25
thinkplot.plot(ts[:n], ys[:n].real, label='real')
thinkplot.plot(ts[:n], ys[:n].imag, label='imag')
thinkplot.save(root='dft1',
xlabel='time (s)',
ylabel='wave',
ylim=[-1.05, 1.05])
ys = synthesize2(amps, freqs, ts)
amps2 = amps * numpy.exp(1.5j)
ys2 = synthesize2(amps2, freqs, ts)
thinkplot.preplot(2)
thinkplot.plot(ts[:n], ys.real[:n], label=r'$\phi_0 = 0$')
thinkplot.plot(ts[:n], ys2.real[:n], label=r'$\phi_0 = 1.5$')
thinkplot.save(root='dft2',
xlabel='time (s)',
ylabel='wave',
ylim=[-1.05, 1.05],
loc='lower right')
framerate = 10000
signal = thinkdsp.SawtoothSignal(freq=500)
wave = signal.make_wave(duration=0.1, framerate=framerate)
hs = dft(wave.ys)
amps = numpy.absolute(hs)
N = len(hs)
fs = numpy.arange(N) * framerate / N
thinkplot.plot(fs, amps)
thinkplot.save(root='dft3',
xlabel='frequency (Hz)',
ylabel='amplitude',
legend=False)
def main():
names = ['date', 'open', 'high', 'low', 'close', 'volume']
df = pd.read_csv('fb.csv', header=0, names=names, parse_dates=[0])
ys = df.close.values[::-1]
close = thinkdsp.Wave(ys, framerate=1)
plot_wave_and_spectrum(close, root='diff_int1')
change = thinkdsp.Wave(np.diff(ys), framerate=1)
plot_wave_and_spectrum(change, root='diff_int2')
plot_filters(close)
plot_diff_deriv(close)
signal = thinkdsp.SawtoothSignal(freq=50)
in_wave = signal.make_wave(duration=0.1, framerate=44100)
plot_sawtooth_and_spectrum(in_wave, 'diff_int6')
out_wave = in_wave.cumsum()
out_wave.unbias()
plot_sawtooth_and_spectrum(out_wave, 'diff_int7')
plot_integral(close)
plot_ratios(in_wave, out_wave)
gaussian = scipy.signal.gaussian(M=11, std=2)
gaussian /= sum(gaussian)
# In[ ]:
names = ['date', 'open', 'high', 'low', 'close', 'volume']
df = pd.read_csv('C:\Users\esehu\Downloads\FB.csv',
header=0,
names=names,
parse_dates=[0])
df.head()
# In[ ]:
signal = thinkdsp.SawtoothSignal(freq=440)
wave = signal.make_wave(duration=1.0, framerate=44100)
wave.make_audio()
# In[ ]:
window = np.ones(11)
window /= sum(window)
thinkplot.plot(window)
# In[ ]:
segment = wave.segment(duration=0.01)
segment.plot()
thinkplot.config(xlabel='Time (s)', ylim=[-1.05, 1.05])
plt.rcParams['font.sans-serif'] = ['SimHei'] #图表上可以显示中文
plt.rcParams['axes.unicode_minus'] = False #图表上可以显示负号
signal = thinkdsp.TriangleSignal(200) #200HZ的三角波
wave = signal.make_wave(duration=0.5, framerate=10000) #长度0.5，每秒10000次
period = signal.period
segment = wave.segment(start=0, duration=period * 3)
plt.subplot(2, 2, 1)
plt.title('200HZ三角波')
segment.plot()
spectrum = wave.make_spectrum()
plt.subplot(2, 2, 2)
plt.title('三角波频谱')
spectrum.plot()
#锯齿波
signal1 = thinkdsp.SawtoothSignal(200)
wave = signal1.make_wave(duration=0.5, framerate=10000)
period = signal1.period
segment = wave.segment(start=0, duration=period * 3)
plt.subplot(2, 2, 3)
plt.title('200HZ锯齿波')
segment.plot()
spectrum = wave.make_spectrum()
plt.subplot(2, 2, 4)
plt.title('锯齿波频谱')
spectrum.plot()
plt.show()
# #close.plot() #pyplot.show() # #cumsum_wav.plot() #pyplot.show() # #cumsum_spec.plot() #pyplot.show() #these operations only work on periodic waves... #inv_close = int_spec.make_wave() #inv_close.plot() #pyplot.show() sq_sig = thinkdsp.SawtoothSignal() sq_wav = sq_sig.make_wave() sq_wav.plot() pyplot.xlim(0, .01) #pyplot.show() cs_wav = sq_wav.cumsum() cs_wav.normalize() cs_wav.unbias() cs_wav.plot() pyplot.xlim(0, .01) #pyplot.show() sq_spec = sq_wav.make_spectrum() int_spec = sq_spec.integrate()
signal = thinkdsp.CosSignal(4500) duration = signal.period * 5 segment = signal.make_wave(duration, framerate=framerate) segment.plot() # In[6]: framerate = 10000 signal = thinkdsp.CosSignal(5500) duration = signal.period * 5 segment = signal.make_wave(duration, framerate=framerate) segment.plot() # In[7]: signal = thinkdsp.SawtoothSignal(500) wave = signal.make_wave(duration=1, framerate=10000) segment = wave.segment(duration=0.005) segment.plot() # In[8]: hs = np.fft.rfft(wave.ys) hs # In[9]: n = len(wave.ys) d = 1 / wave.framerate fs = np.fft.rfftfreq(n, d) fs
signal_tri.plot() wave = signal_tri.make_wave(duration=0.01, framerate=10000) spectrum = wave.make_spectrum() plt.subplot(334) spectrum.plot() s = af(spectrum) plt.subplot(337) s.plot() signal_squ = thinkdsp.SquareSignal(200) #生成一个200Hz的三角波 plt.subplot(332) signal_squ.plot() wave = signal_squ.make_wave(duration=0.01, framerate=10000) spectrum = wave.make_spectrum() plt.subplot(335) spectrum.plot() s = af(spectrum) plt.subplot(338) s.plot() signal_saw = thinkdsp.SawtoothSignal(200) #生成一个200Hz的锯齿波 plt.subplot(333) signal_saw.plot() wave = signal_saw.make_wave(duration=0.01, framerate=10000) spectrum = wave.make_spectrum() plt.subplot(336) spectrum.plot() s = af(spectrum) plt.subplot(339) s.plot() plt.show()
