def plot_amen2():
wave = thinkdsp.read_wave('263868__kevcio__amen-break-a-160-bpm.wav')
wave.normalize()
ax1 = thinkplot.preplot(6, rows=4)
wave.make_spectrum(full=True).plot(label='spectrum')
xlim = [-22050 - 250, 22050]
thinkplot.config(xlim=xlim, xticklabels='invisible')
ax2 = thinkplot.subplot(2)
impulses = make_impulses(wave, 4)
impulses.make_spectrum(full=True).plot(label='impulses')
thinkplot.config(xlim=xlim, xticklabels='invisible')
ax3 = thinkplot.subplot(3)
sampled = wave * impulses
spectrum = sampled.make_spectrum(full=True)
spectrum.plot(label='sampled')
thinkplot.config(xlim=xlim, xticklabels='invisible')
ax4 = thinkplot.subplot(4)
spectrum.low_pass(5512.5)
spectrum.plot(label='filtered')
thinkplot.config(xlim=xlim, xlabel='Frequency (Hz)')
thinkplot.save(root='sampling4', formats=FORMATS)
def main():
# make_figures()
wave = thinkdsp.read_wave('28042__bcjordan__voicedownbew.wav')
wave.unbias()
wave.normalize()
track_pitch(wave)
return
thinkplot.preplot(rows=1, cols=2)
plot_shifted(wave, 0.0003)
thinkplot.config(xlabel='time (s)',
ylabel='amplitude',
ylim=[-1, 1])
thinkplot.subplot(2)
plot_shifted(wave, 0.00225)
thinkplot.config(xlabel='time (s)',
ylim=[-1, 1])
thinkplot.save(root='autocorr3')
def plot_amen2():
wave = thinkdsp.read_wave('263868__kevcio__amen-break-a-160-bpm.wav')
wave.normalize()
ax1 = thinkplot.preplot(6, rows=4)
wave.make_spectrum(full=True).plot(label='spectrum')
xlim = [-22050-250, 22050]
thinkplot.config(xlim=xlim, xticklabels='invisible')
ax2 = thinkplot.subplot(2)
impulses = make_impulses(wave, 4)
impulses.make_spectrum(full=True).plot(label='impulses')
thinkplot.config(xlim=xlim, xticklabels='invisible')
ax3 = thinkplot.subplot(3)
sampled = wave * impulses
spectrum = sampled.make_spectrum(full=True)
spectrum.plot(label='sampled')
thinkplot.config(xlim=xlim, xticklabels='invisible')
ax4 = thinkplot.subplot(4)
spectrum.low_pass(5512.5)
spectrum.plot(label='filtered')
thinkplot.config(xlim=xlim, xlabel='Frequency (Hz)')
thinkplot.save(root='sampling4',
formats=FORMATS)
def plot_filters(close):
"""Plots the filter that corresponds to diff, deriv, and integral.
"""
thinkplot.preplot(3, cols=2)
diff_window = np.array([1.0, -1.0])
diff_filter = make_filter(diff_window, close)
diff_filter.plot(label='diff')
deriv_filter = close.make_spectrum()
deriv_filter.hs = PI2 * 1j * deriv_filter.fs
deriv_filter.plot(label='derivative')
thinkplot.config(xlabel='Frequency (1/day)',
ylabel='Amplitude ratio',
loc='upper left')
thinkplot.subplot(2)
integ_filter = deriv_filter.copy()
integ_filter.hs = 1 / (PI2 * 1j * integ_filter.fs)
integ_filter.plot(label='integral')
thinkplot.config(xlabel='Frequency (1/day)',
ylabel='Amplitude ratio',
yscale='log')
thinkplot.save('diff_int3')
def plot_response():
thinkplot.preplot(cols=2)
response = thinkdsp.read_wave('180961__kleeb__gunshots.wav')
response = response.segment(start=0.26, duration=5.0)
response.normalize()
response.plot()
thinkplot.config(xlabel='time',
xlim=[0, 5.0],
ylabel='amplitude',
ylim=[-1.05, 1.05])
thinkplot.subplot(2)
transfer = response.make_spectrum()
transfer.plot()
thinkplot.config(xlabel='frequency', xlim=[0, 22500], ylabel='amplitude')
thinkplot.save(root='systems6')
wave = thinkdsp.read_wave('92002__jcveliz__violin-origional.wav')
wave.ys = wave.ys[:len(response)]
wave.normalize()
spectrum = wave.make_spectrum()
output = (spectrum * transfer).make_wave()
output.normalize()
wave.plot(color='0.7')
output.plot(alpha=0.4)
thinkplot.config(xlabel='time',
xlim=[0, 5.0],
ylabel='amplitude',
ylim=[-1.05, 1.05])
thinkplot.save(root='systems7')
def chirp_spectrum():
"""Plots the spectrum of a one-second one-octave linear chirp.
"""
signal = thinkdsp.Chirp(start=220, end=440)
wave = signal.make_wave(duration=1)
thinkplot.preplot(3, cols=3)
duration = 0.01
wave.segment(0, duration).plot()
thinkplot.config(ylim=[-1.05, 1.05])
thinkplot.subplot(2)
wave.segment(0.5, duration).plot()
thinkplot.config(yticklabels='invisible',
xlabel='Time (s)')
thinkplot.subplot(3)
wave.segment(0.9, duration).plot()
thinkplot.config(yticklabels='invisible')
thinkplot.save('chirp3')
spectrum = wave.make_spectrum()
spectrum.plot(high=700)
thinkplot.save('chirp1',
xlabel='Frequency (Hz)',
ylabel='Amplitude')
def plot_response():
thinkplot.preplot(cols=2)
response = thinkdsp.read_wave("180961__kleeb__gunshots.wav")
response = response.segment(start=0.26, duration=5.0)
response.normalize()
response.plot()
thinkplot.config(xlabel="time", xlim=[0, 5.0], ylabel="amplitude", ylim=[-1.05, 1.05])
thinkplot.subplot(2)
transfer = response.make_spectrum()
transfer.plot()
thinkplot.config(xlabel="frequency", xlim=[0, 22500], ylabel="amplitude")
thinkplot.save(root="systems6")
wave = thinkdsp.read_wave("92002__jcveliz__violin-origional.wav")
wave.ys = wave.ys[: len(response)]
wave.normalize()
spectrum = wave.make_spectrum()
output = (spectrum * transfer).make_wave()
output.normalize()
wave.plot(color="0.7")
output.plot(alpha=0.4)
thinkplot.config(xlabel="time", xlim=[0, 5.0], ylabel="amplitude", ylim=[-1.05, 1.05])
thinkplot.save(root="systems7")
def triangle_example(freq):
"""Makes a figure showing a triangle wave.
freq: frequency in Hz
"""
framerate = 10000
signal = thinkdsp.TriangleSignal(freq)
duration = signal.period*3
segment = signal.make_wave(duration, framerate=framerate)
segment.plot()
thinkplot.save(root='triangle-%d-1' % freq,
xlabel='Time (s)',
axis=[0, duration, -1.05, 1.05])
wave = signal.make_wave(duration=0.5, framerate=framerate)
spectrum = wave.make_spectrum()
thinkplot.preplot(cols=2)
spectrum.plot()
thinkplot.config(xlabel='Frequency (Hz)',
ylabel='Amplitude')
thinkplot.subplot(2)
spectrum.plot()
thinkplot.config(ylim=[0, 500],
xlabel='Frequency (Hz)')
thinkplot.save(root='triangle-%d-2' % freq)
def aliasing_example(offset=0.000003):
"""Makes a figure showing the effect of aliasing.
"""
framerate = 10000
def plot_segment(freq):
signal = thinkdsp.CosSignal(freq)
duration = signal.period*4
thinkplot.Hlines(0, 0, duration, color='gray')
segment = signal.make_wave(duration, framerate=framerate*10)
segment.plot(linewidth=0.5, color='gray')
segment = signal.make_wave(duration, framerate=framerate)
segment.plot_vlines(label=freq, linewidth=4)
thinkplot.preplot(rows=2)
plot_segment(4500)
thinkplot.config(axis=[-0.00002, 0.0007, -1.05, 1.05])
thinkplot.subplot(2)
plot_segment(5500)
thinkplot.config(axis=[-0.00002, 0.0007, -1.05, 1.05])
thinkplot.save(root='aliasing1',
xlabel='Time (s)',
formats=FORMATS)
def chirp_spectrum():
"""Plots the spectrum of a one-second one-octave linear chirp.
"""
signal = thinkdsp.Chirp(start=220, end=440)
wave = signal.make_wave(duration=1)
thinkplot.preplot(3, cols=3)
duration = 0.01
wave.segment(0, duration).plot()
thinkplot.config(ylim=[-1.05, 1.05])
thinkplot.subplot(2)
wave.segment(0.5, duration).plot()
thinkplot.config(yticklabels='invisible',
xlabel='Time (s)')
thinkplot.subplot(3)
wave.segment(0.9, duration).plot()
thinkplot.config(yticklabels='invisible')
thinkplot.save('chirp3')
spectrum = wave.make_spectrum()
spectrum.plot(high=700)
thinkplot.save('chirp1',
xlabel='Frequency (Hz)')
def triangle_example(freq):
"""Makes a figure showing a triangle wave.
freq: frequency in Hz
"""
framerate = 10000
signal = thinkdsp.TriangleSignal(freq)
duration = signal.period * 3
segment = signal.make_wave(duration, framerate=framerate)
segment.plot()
thinkplot.save(root='triangle-%d-1' % freq,
xlabel='Time (s)',
axis=[0, duration, -1.05, 1.05])
wave = signal.make_wave(duration=0.5, framerate=framerate)
spectrum = wave.make_spectrum()
thinkplot.preplot(cols=2)
spectrum.plot()
thinkplot.config(xlabel='Frequency (Hz)', ylabel='Amplitude')
thinkplot.subplot(2)
spectrum.plot()
thinkplot.config(ylim=[0, 500], xlabel='Frequency (Hz)')
thinkplot.save(root='triangle-%d-2' % freq)
def plot_filters(close):
"""Plots the filter that corresponds to diff, deriv, and integral.
"""
thinkplot.preplot(3, cols=2)
diff_window = np.array([1.0, -1.0])
diff_filter = make_filter(diff_window, close)
diff_filter.plot(label='diff')
deriv_filter = close.make_spectrum()
deriv_filter.hs = PI2 * 1j * deriv_filter.fs
deriv_filter.plot(label='derivative')
thinkplot.config(xlabel='Frequency (1/day)',
ylabel='Amplitude ratio',
loc='upper left')
thinkplot.subplot(2)
integ_filter = deriv_filter.copy()
integ_filter.hs = 1 / (PI2 * 1j * integ_filter.fs)
integ_filter.plot(label='integral')
thinkplot.config(xlabel='Frequency (1/day)',
ylabel='Amplitude ratio',
yscale='log')
thinkplot.save('diff_int3')
def process_noise(signal, root='white'):
"""Plots wave and spectrum for noise signals.
signal: Signal
root: string used to generate file names
"""
framerate = 11025
wave = signal.make_wave(duration=0.5, framerate=framerate)
# 0: waveform
segment = wave.segment(duration=0.1)
segment.plot(linewidth=1, alpha=0.5)
thinkplot.save(root=root+'noise0',
xlabel='Time (s)',
ylim=[-1.05, 1.05])
spectrum = wave.make_spectrum()
# 1: spectrum
spectrum.plot_power(linewidth=1, alpha=0.5)
thinkplot.save(root=root+'noise1',
xlabel='Frequency (Hz)',
ylabel='Power',
xlim=[0, spectrum.fs[-1]])
slope, _, _, _, _ = spectrum.estimate_slope()
print('estimated slope', slope)
# 2: integrated spectrum
integ = spectrum.make_integrated_spectrum()
integ.plot_power()
thinkplot.save(root=root+'noise2',
xlabel='Frequency (Hz)',
ylabel='Cumulative fraction of total power',
xlim=[0, framerate/2])
# 3: log-log power spectrum
spectrum.hs[0] = 0
thinkplot.preplot(cols=2)
spectrum.plot_power(linewidth=1, alpha=0.5)
thinkplot.config(xlabel='Frequency (Hz)',
ylabel='Power',
xlim=[0, framerate/2])
thinkplot.subplot(2)
spectrum.plot_power(linewidth=1, alpha=0.5)
thinkplot.config(xlabel='Frequency (Hz)',
xscale='log',
yscale='log',
xlim=[0, framerate/2])
thinkplot.save(root=root+'noise3')
def plot_wave_and_spectrum(wave, root):
"""Makes a plot showing
"""
thinkplot.preplot(cols=2)
wave.plot()
thinkplot.config(xlabel="days", xlim=[0, 1650], ylabel="dollars", legend=False)
thinkplot.subplot(2)
spectrum = wave.make_spectrum()
print(spectrum.estimate_slope())
spectrum.plot()
thinkplot.config(xlabel="frequency (1/days)", ylabel="power", xscale="log", yscale="log", legend=False)
thinkplot.save(root=root)
def process_noise(signal, root='white'):
"""Plots wave and spectrum for noise signals.
signal: Signal
root: string used to generate file names
"""
framerate = 48000
wave = signal.make_wave(duration=0.5, framerate=framerate)
# 0: waveform
segment = wave.segment(duration=0.1)
segment.plot(linewidth=1, alpha=0.5)
thinkplot.save(root=root + 'noise0', xlabel='Time (s)', ylim=[-1.05, 1.05])
spectrum = wave.make_spectrum()
# 1: spectrum
spectrum.plot_power(linewidth=1, alpha=0.5)
thinkplot.save(root=root + 'noise1',
xlabel='Frequency (Hz)',
ylabel='Power',
xlim=[0, spectrum.fs[-1]])
slope, _, _, _, _ = spectrum.estimate_slope()
print('estimated slope', slope)
# 2: integrated spectrum
integ = spectrum.make_integrated_spectrum()
integ.plot_power()
thinkplot.save(root=root + 'noise2',
xlabel='Frequency (Hz)',
ylabel='Cumulative fraction of total power',
xlim=[0, framerate / 2])
# 3: log-log power spectrum
spectrum.hs[0] = 0
thinkplot.preplot(cols=2)
spectrum.plot_power(linewidth=1, alpha=0.5)
thinkplot.config(xlabel='Frequency (Hz)',
ylabel='Power',
xlim=[0, framerate / 2])
thinkplot.subplot(2)
spectrum.plot_power(linewidth=1, alpha=0.5)
thinkplot.config(xlabel='Frequency (Hz)',
xscale='log',
yscale='log',
xlim=[0, framerate / 2])
thinkplot.save(root=root + 'noise3')
def plot_sawtooth_and_spectrum(wave, root):
"""Makes a plot showing a sawtoothwave and its spectrum.
"""
thinkplot.preplot(cols=2)
wave.plot()
thinkplot.config(xlabel='Time (s)')
thinkplot.subplot(2)
spectrum = wave.make_spectrum()
spectrum.plot()
thinkplot.config(xlabel='Frequency (Hz)',
ylabel='Amplitude',
xlim=[0, spectrum.fs[-1]])
thinkplot.save(root)
def plot_sawtooth_and_spectrum(wave, root):
"""Makes a plot showing a sawtoothwave and its spectrum.
"""
thinkplot.preplot(cols=2)
wave.plot()
thinkplot.config(xlabel='Time (s)')
thinkplot.subplot(2)
spectrum = wave.make_spectrum()
spectrum.plot()
thinkplot.config(xlabel='Frequency (Hz)',
ylabel='Amplitude',
xlim=[0, spectrum.fs[-1]])
thinkplot.save(root)
def plot_sincs(wave):
start = 1.0
duration = 0.01
factor = 4
short = wave.segment(start=start, duration=duration)
#short.plot()
sampled = sample(short, factor)
#sampled.plot_vlines(color='gray')
spectrum = sampled.make_spectrum(full=True)
boxcar = make_boxcar(spectrum, factor)
sinc = boxcar.make_wave()
sinc.shift(sampled.ts[0])
sinc.roll(len(sinc)//2)
thinkplot.preplot(2, cols=2)
sinc.plot()
thinkplot.config(xlabel='Time (s)')
thinkplot.subplot(2)
boxcar.plot()
thinkplot.config(xlabel='Frequency (Hz)',
ylim=[0, 1.05],
xlim=[-boxcar.max_freq, boxcar.max_freq])
thinkplot.save(root='sampling6',
formats=FORMATS)
return
# CAUTION: don't call plot_sinc_demo with a large wave or it will
# fill memory and crash
plot_sinc_demo(short, 4)
thinkplot.config(xlabel='Time (s)')
thinkplot.save(root='sampling7',
formats=FORMATS)
start = short.start + 0.004
duration = 0.00061
plot_sinc_demo(short, 4, start, duration)
thinkplot.config(xlabel='Time (s)',
xlim=[start, start+duration],
ylim=[-0.06, 0.17], legend=False)
thinkplot.save(root='sampling8',
formats=FORMATS)
def show_impulses(wave, factor, i):
thinkplot.subplot(i)
thinkplot.preplot(2)
impulses = make_impulses(wave, factor)
impulses.segment(0, 0.001).plot_vlines(linewidth=2, xfactor=1000)
if i == 1:
thinkplot.config(title='Impulse train', ylim=[0, 1.05])
else:
thinkplot.config(xlabel='Time (ms)', ylim=[0, 1.05])
thinkplot.subplot(i + 1)
impulses.make_spectrum(full=True).plot()
kill_yticklabels()
if i == 1:
thinkplot.config(title='DFT of impulse train', xlim=[-22400, 22400])
else:
thinkplot.config(xlabel='Frequency (Hz)', xlim=[-22400, 22400])
def generate_pmf(fb, hk):
pmf_fb = Pmf(degrees(fb))
pmf_hk = Pmf(degrees(hk))
thinkplot.preplot(cols=2)
thinkplot.plot([30, 2000], [5e-2, 2e-4], color='gray', linestyle='dashed')
thinkplot.Pdf(pmf_fb, style='.', label='Facebook')
thinkplot.config(xscale='log', yscale='log', xlabel='degree', ylabel='PMF')
thinkplot.subplot(2)
thinkplot.plot([55, 500], [5e-2, 2e-4], color='gray', linestyle='dashed')
thinkplot.Pdf(pmf_hk, style='.', label='HK graph')
thinkplot.config(xscale='log', yscale='log', xlabel='degree', ylabel='PMF')
plt.savefig('PMFGraphs_Original.png')
def plot_sampling3(wave, root):
ax1 = thinkplot.preplot(6, rows=3)
wave.make_spectrum(full=True).plot(label='spectrum')
thinkplot.config(xlim=XLIM, xticklabels='invisible')
impulses = make_impulses(wave, 4)
ax2 = thinkplot.subplot(2)
sampled = wave * impulses
spectrum = sampled.make_spectrum(full=True)
spectrum.plot(label='sampled')
thinkplot.config(xlim=XLIM, xticklabels='invisible')
ax3 = thinkplot.subplot(3)
spectrum.low_pass(5512.5)
spectrum.plot(label='filtered')
thinkplot.config(xlim=XLIM, xlabel='Frequency (Hz)')
thinkplot.save(root=root, formats=FORMATS)
def plot_response(response):
"""Plots an input wave and the corresponding output.
"""
thinkplot.preplot(cols=2)
response.plot()
thinkplot.config(xlabel='Time (s)',
xlim=[0.26, response.end],
ylim=[-1.05, 1.05])
thinkplot.subplot(2)
transfer = response.make_spectrum()
transfer.plot()
thinkplot.config(xlabel='Frequency (Hz)',
xlim=[0, 22500],
ylabel='Amplitude')
thinkplot.save(root='systems6')
violin = thinkdsp.read_wave('92002__jcveliz__violin-origional.wav')
start = 0.11
violin = violin.segment(start=start)
violin.shift(-start)
violin.truncate(len(response))
violin.normalize()
spectrum = violin.make_spectrum()
output = (spectrum * transfer).make_wave()
output.normalize()
thinkplot.preplot(rows=2)
violin.plot(label='input')
thinkplot.config(xlim=[0, violin.end],
ylim=[-1.05, 1.05])
thinkplot.subplot(2)
output.plot(label='output')
thinkplot.config(xlabel='Time (s)',
xlim=[0, violin.end],
ylim=[-1.05, 1.05])
thinkplot.save(root='systems7')
def plot_sampling3(wave, root):
ax1 = thinkplot.preplot(6, rows=3)
wave.make_spectrum(full=True).plot(label='spectrum')
thinkplot.config(xlim=XLIM, xticklabels='invisible')
impulses = make_impulses(wave, 4)
ax2 = thinkplot.subplot(2)
sampled = wave * impulses
spectrum = sampled.make_spectrum(full=True)
spectrum.plot(label='sampled')
thinkplot.config(xlim=XLIM, xticklabels='invisible')
ax3 = thinkplot.subplot(3)
spectrum.low_pass(5512.5)
spectrum.plot(label='filtered')
thinkplot.config(xlim=XLIM, xlabel='Frequency (Hz)')
thinkplot.save(root=root,
formats=FORMATS)
def plot_response(response):
"""Plots an input wave and the corresponding output.
"""
thinkplot.preplot(cols=2)
response.plot()
thinkplot.config(xlabel='Time (s)',
xlim=[0.26, response.end],
ylim=[-1.05, 1.05])
thinkplot.subplot(2)
transfer = response.make_spectrum()
transfer.plot()
thinkplot.config(xlabel='Frequency (Hz)',
xlim=[0, 22500],
ylabel='Amplitude')
thinkplot.save(root='systems6')
violin = thinkdsp.read_wave('92002__jcveliz__violin-origional.wav')
start = 0.11
violin = violin.segment(start=start)
violin.shift(-start)
violin.truncate(len(response))
violin.normalize()
spectrum = violin.make_spectrum()
output = (spectrum * transfer).make_wave()
output.normalize()
thinkplot.preplot(rows=2)
violin.plot(label='input')
thinkplot.config(xlim=[0, violin.end], ylim=[-1.05, 1.05])
thinkplot.subplot(2)
output.plot(label='output')
thinkplot.config(xlabel='Time (s)',
xlim=[0, violin.end],
ylim=[-1.05, 1.05])
thinkplot.save(root='systems7')
def plot_wave_and_spectrum(wave, root):
"""Makes a plot showing a wave and its spectrum.
wave: Wave object
root: string used to generate filenames
"""
thinkplot.preplot(cols=2)
wave.plot()
thinkplot.config(xlabel='Time (days)', ylabel='Price ($)')
thinkplot.subplot(2)
spectrum = wave.make_spectrum()
print(spectrum.estimate_slope())
spectrum.plot()
thinkplot.config(xlabel='Frequency (1/days)',
ylabel='Amplitude',
xlim=[0, spectrum.fs[-1]],
xscale='log',
yscale='log')
thinkplot.save(root=root)
def show_impulses(wave, factor, i):
thinkplot.subplot(i)
thinkplot.preplot(2)
impulses = make_impulses(wave, factor)
impulses.segment(0, 0.001).plot_vlines(linewidth=2)
if i == 1:
thinkplot.config(title='Impulse train',
ylim=[0, 1.05])
else:
thinkplot.config(xlabel='Time (s)',
ylim=[0, 1.05])
thinkplot.subplot(i+1)
impulses.make_spectrum(full=True).plot()
kill_yticklabels()
if i == 1:
thinkplot.config(title='DFT of impulse train',
xlim=[-22400, 22400])
else:
thinkplot.config(xlabel='Frequency (Hz)',
xlim=[-22400, 22400])
def plot_wave_and_spectrum(wave, root):
"""Makes a plot showing
"""
thinkplot.preplot(cols=2)
wave.plot()
thinkplot.config(xlabel='days',
xlim=[0, 1650],
ylabel='dollars',
legend=False)
thinkplot.subplot(2)
spectrum = wave.make_spectrum()
print(spectrum.estimate_slope())
spectrum.plot()
thinkplot.config(xlabel='frequency (1/days)',
ylabel='power',
xscale='log',
yscale='log',
legend=False)
thinkplot.save(root=root)
def plot_sampling(wave, root):
ax1 = thinkplot.preplot(2, rows=2)
wave.make_spectrum(full=True).plot(label='spectrum')
thinkplot.config(xlim=XLIM, xticklabels='invisible')
ax2 = thinkplot.subplot(2)
sampled = sample(wave, 4)
sampled.make_spectrum(full=True).plot(label='sampled')
thinkplot.config(xlim=XLIM, xlabel='Frequency (Hz)')
thinkplot.save(root=root, formats=FORMATS)
def window_plot():
"""Makes a plot showing a sinusoid, hamming window, and their product.
"""
signal = thinkdsp.SinSignal(freq=440)
duration = signal.period * 10.25
wave1 = signal.make_wave(duration)
wave2 = signal.make_wave(duration)
ys = np.hamming(len(wave1.ys))
ts = wave1.ts
window = thinkdsp.Wave(ys, ts, wave1.framerate)
wave2.hamming()
thinkplot.preplot(rows=3, cols=1)
pyplot.subplots_adjust(wspace=0.3, hspace=0.3,
right=0.95, left=0.1,
top=0.95, bottom=0.05)
thinkplot.subplot(1)
wave1.plot()
thinkplot.config(axis=[0, duration, -1.07, 1.07])
thinkplot.subplot(2)
window.plot()
thinkplot.config(axis=[0, duration, -1.07, 1.07])
thinkplot.subplot(3)
wave2.plot()
thinkplot.config(axis=[0, duration, -1.07, 1.07],
xlabel='Time (s)')
thinkplot.save(root='windowing2')
def window_plot():
"""Makes a plot showing a sinusoid, hamming window, and their product.
"""
signal = thinkdsp.SinSignal(freq=440)
duration = signal.period * 10.25
wave1 = signal.make_wave(duration)
wave2 = signal.make_wave(duration)
ys = numpy.hamming(len(wave1.ys))
window = thinkdsp.Wave(ys, wave1.framerate)
wave2.hamming()
thinkplot.preplot(rows=3, cols=1)
pyplot.subplots_adjust(wspace=0.3,
hspace=0.3,
right=0.95,
left=0.1,
top=0.95,
bottom=0.05)
thinkplot.subplot(1)
wave1.plot()
thinkplot.config(axis=[0, duration, -1.07, 1.07])
thinkplot.subplot(2)
window.plot()
thinkplot.config(axis=[0, duration, -1.07, 1.07])
thinkplot.subplot(3)
wave2.plot()
thinkplot.config(axis=[0, duration, -1.07, 1.07], xlabel='time (s)')
thinkplot.save(root='windowing2')
def three_spectrums():
"""Makes a plot showing three spectrums for a sinusoid.
"""
thinkplot.preplot(rows=1, cols=3)
pyplot.subplots_adjust(wspace=0.3,
hspace=0.4,
right=0.95,
left=0.1,
top=0.95,
bottom=0.05)
xticks = range(0, 900, 200)
thinkplot.subplot(1)
thinkplot.config(xticks=xticks)
discontinuity(num_periods=30, hamming=False)
thinkplot.subplot(2)
thinkplot.config(xticks=xticks)
discontinuity(num_periods=30.25, hamming=False)
thinkplot.subplot(3)
thinkplot.config(xticks=xticks)
discontinuity(num_periods=30.25, hamming=True)
thinkplot.save(root='windowing1')
def plot_gaussian_noise():
"""Shows the distribution of the spectrum of Gaussian noise.
"""
thinkdsp.random_seed(18)
signal = thinkdsp.UncorrelatedGaussianNoise()
wave = signal.make_wave(duration=0.5, framerate=11025)
spectrum = wave.make_spectrum()
thinkplot.preplot(2, cols=2)
thinkstats2.NormalProbabilityPlot(spectrum.real, label='real')
thinkplot.config(xlabel='Normal sample',
ylabel='Amplitude',
ylim=[-250, 250],
loc='lower right')
thinkplot.subplot(2)
thinkstats2.NormalProbabilityPlot(spectrum.imag, label='imag')
thinkplot.config(xlabel='Normal sample',
ylim=[-250, 250],
loc='lower right')
thinkplot.save(root='noise1')
def plot_gaussian_noise():
"""Shows the distribution of the spectrum of Gaussian noise.
"""
thinkdsp.random_seed(18)
signal = thinkdsp.UncorrelatedGaussianNoise()
wave = signal.make_wave(duration=0.5, framerate=48000)
spectrum = wave.make_spectrum()
thinkplot.preplot(2, cols=2)
thinkstats2.NormalProbabilityPlot(spectrum.real, label='real')
thinkplot.config(xlabel='Normal sample',
ylabel='Amplitude',
ylim=[-250, 250],
loc='lower right')
thinkplot.subplot(2)
thinkstats2.NormalProbabilityPlot(spectrum.imag, label='imag')
thinkplot.config(xlabel='Normal sample',
ylim=[-250, 250],
loc='lower right')
thinkplot.save(root='noise1')
def plot_sampling(wave, root):
ax1 = thinkplot.preplot(2, rows=2)
wave.make_spectrum(full=True).plot(label='spectrum')
thinkplot.config(xlim=XLIM, xticklabels='invisible')
ax2 = thinkplot.subplot(2)
sampled = sample(wave, 4)
sampled.make_spectrum(full=True).plot(label='sampled')
thinkplot.config(xlim=XLIM, xlabel='Frequency (Hz)')
thinkplot.save(root=root,
formats=FORMATS)
def plot_wave_and_spectrum(wave, root):
"""Makes a plot showing a wave and its spectrum.
wave: Wave object
root: string used to generate filenames
"""
thinkplot.preplot(cols=2)
wave.plot()
thinkplot.config(xlabel='Time (days)',
ylabel='Price ($)')
thinkplot.subplot(2)
spectrum = wave.make_spectrum()
print(spectrum.estimate_slope())
spectrum.plot()
thinkplot.config(xlabel='Frequency (1/days)',
ylabel='Amplitude',
xlim=[0, spectrum.fs[-1]],
xscale='log',
yscale='log')
thinkplot.save(root=root)
def plot_am():
wave = thinkdsp.read_wave('105977__wcfl10__favorite-station.wav')
wave.unbias()
wave.normalize()
# top
ax1 = thinkplot.preplot(6, rows=4)
spectrum = wave.make_spectrum(full=True)
spectrum.plot(label='wave')
xlim = [-22050, 22050]
thinkplot.config(xlim=xlim, xticklabels='invisible')
#second
carrier_sig = thinkdsp.CosSignal(freq=10000)
carrier_wave = carrier_sig.make_wave(duration=wave.duration,
framerate=wave.framerate)
modulated = wave * carrier_wave
ax2 = thinkplot.subplot(2, sharey=ax1)
modulated.make_spectrum(full=True).plot(label='modulated')
thinkplot.config(xlim=xlim, xticklabels='invisible')
# third
demodulated = modulated * carrier_wave
demodulated_spectrum = demodulated.make_spectrum(full=True)
ax3 = thinkplot.subplot(3, sharey=ax1)
demodulated_spectrum.plot(label='demodulated')
thinkplot.config(xlim=xlim, xticklabels='invisible')
#fourth
ax4 = thinkplot.subplot(4, sharey=ax1)
demodulated_spectrum.low_pass(10000)
demodulated_spectrum.plot(label='filtered')
thinkplot.config(xlim=xlim, xlabel='Frequency (Hz)')
thinkplot.save(root='sampling2',
formats=FORMATS)
def plot_filter(M=11, std=2):
signal = thinkdsp.SquareSignal(freq=440)
wave = signal.make_wave(duration=1, framerate=44100)
spectrum = wave.make_spectrum()
gaussian = scipy.signal.gaussian(M=M, std=std)
gaussian /= sum(gaussian)
high = gaussian.max()
thinkplot.preplot(cols=2)
thinkplot.plot(gaussian)
thinkplot.config(xlabel='Index',
ylabel='Window',
xlim=[0, len(gaussian) - 1],
ylim=[0, 1.1 * high])
ys = np.convolve(wave.ys, gaussian, mode='same')
smooth = thinkdsp.Wave(ys, framerate=wave.framerate)
spectrum2 = smooth.make_spectrum()
# plot the ratio of the original and smoothed spectrum
amps = spectrum.amps
amps2 = spectrum2.amps
ratio = amps2 / amps
ratio[amps < 560] = 0
# plot the same ratio along with the FFT of the window
padded = thinkdsp.zero_pad(gaussian, len(wave))
dft_gaussian = np.fft.rfft(padded)
thinkplot.subplot(2)
thinkplot.plot(abs(dft_gaussian), color=GRAY, label='Gaussian filter')
thinkplot.plot(ratio, label='amplitude ratio')
thinkplot.show(xlabel='Frequency (Hz)',
ylabel='Amplitude ratio',
xlim=[0, 22050],
ylim=[0, 1.05])
def plot_am():
wave = thinkdsp.read_wave('105977__wcfl10__favorite-station.wav')
wave.unbias()
wave.normalize()
# top
ax1 = thinkplot.preplot(6, rows=4)
spectrum = wave.make_spectrum(full=True)
spectrum.plot(label='wave')
xlim = [-22050, 22050]
thinkplot.config(xlim=xlim, xticklabels='invisible')
#second
carrier_sig = thinkdsp.CosSignal(freq=10000)
carrier_wave = carrier_sig.make_wave(duration=wave.duration,
framerate=wave.framerate)
modulated = wave * carrier_wave
ax2 = thinkplot.subplot(2, sharey=ax1)
modulated.make_spectrum(full=True).plot(label='modulated')
thinkplot.config(xlim=xlim, xticklabels='invisible')
# third
demodulated = modulated * carrier_wave
demodulated_spectrum = demodulated.make_spectrum(full=True)
ax3 = thinkplot.subplot(3, sharey=ax1)
demodulated_spectrum.plot(label='demodulated')
thinkplot.config(xlim=xlim, xticklabels='invisible')
#fourth
ax4 = thinkplot.subplot(4, sharey=ax1)
demodulated_spectrum.low_pass(10000)
demodulated_spectrum.plot(label='filtered')
thinkplot.config(xlim=xlim, xlabel='Frequency (Hz)')
thinkplot.save(root='sampling2', formats=FORMATS)
def aliasing_example(offset=0.000003):
"""Makes a figure showing the effect of aliasing.
"""
framerate = 10000
def plot_segment(freq):
signal = thinkdsp.CosSignal(freq)
duration = signal.period * 4
thinkplot.Hlines(0, 0, duration, color='gray')
segment = signal.make_wave(duration, framerate=framerate * 10)
segment.plot(linewidth=0.5, color='gray')
segment = signal.make_wave(duration, framerate=framerate)
segment.plot_vlines(label=freq, linewidth=4)
thinkplot.preplot(rows=2)
plot_segment(4500)
thinkplot.config(axis=[-0.00002, 0.0007, -1.05, 1.05])
thinkplot.subplot(2)
plot_segment(5500)
thinkplot.config(axis=[-0.00002, 0.0007, -1.05, 1.05])
thinkplot.save(root='aliasing1', xlabel='Time (s)', formats=FORMATS)
def plot_amen():
wave = thinkdsp.read_wave('263868__kevcio__amen-break-a-160-bpm.wav')
wave.normalize()
ax1 = thinkplot.preplot(2, rows=2)
wave.make_spectrum(full=True).plot()
xlim = [-22050, 22050]
thinkplot.config(xlim=xlim, xticklabels='invisible')
ax2 = thinkplot.subplot(2, sharey=ax1)
sampled = sample(wave, 4)
sampled.make_spectrum(full=True).plot()
thinkplot.config(xlim=xlim, xlabel='Frequency (Hz)')
thinkplot.show()
return
def plot_amen():
wave = thinkdsp.read_wave('263868__kevcio__amen-break-a-160-bpm.wav')
wave.normalize()
ax1 = thinkplot.preplot(2, rows=2)
wave.make_spectrum(full=True).plot()
xlim = [-22050, 22050]
thinkplot.config(xlim=xlim, xticklabels='invisible')
ax2 = thinkplot.subplot(2, sharey=ax1)
sampled = sample(wave, 4)
sampled.make_spectrum(full=True).plot()
thinkplot.config(xlim=xlim, xlabel='Frequency (Hz)')
thinkplot.show()
return
def three_spectrums():
"""Makes a plot showing three spectrums for a sinusoid.
"""
thinkplot.preplot(rows=1, cols=3)
pyplot.subplots_adjust(wspace=0.3, hspace=0.4, right=0.95, left=0.1, top=0.95, bottom=0.05)
xticks = xrange(0, 900, 200)
thinkplot.subplot(1)
thinkplot.config(xticks=xticks)
discontinuity(num_periods=30, hamming=False)
thinkplot.subplot(2)
thinkplot.config(xticks=xticks)
discontinuity(num_periods=30.25, hamming=False)
thinkplot.subplot(3)
thinkplot.config(xticks=xticks)
discontinuity(num_periods=30.25, hamming=True)
thinkplot.save(root="windowing1")
thinkplot.Config(xlabel = 'Total Revenue', ylabel = 'PMF') # In[54]: thinkplot.Pmf(flfindistdfpmf) thinkplot.Pmf(vfindistdfpmf) # In[55]: thinkplot.PrePlot(2) thinkplot.subplot(2) #axis = [0, 800, 0, 0.0005] thinkplot.Pmfs([flfindistdfpmf,vfindistdfpmf ]) thinkplot.Show(xlabel = 'Total Revenue', ylabel = 'PMF') # # Lets plot PMF of log transformed columns # In[56]: findistdf.columns # In[57]:
from __future__ import print_function, division
import sys
sys.path.append('../code')
import thinkdsp
import thinkplot
import numpy as np
N = 100
n = np.arange(1, N)
thinkplot.preplot(rows=1, cols=3)
thinkplot.subplot(1)
thinkplot.plot(n, n**3, label='n**3', linewidth=1, color='r')
thinkplot.plot(n, n**2, label='n**2', linewidth=1, color='b')
thinkplot.plot(n, n * np.log(n), label='n*log(n)', linewidth=1, color='g')
thinkplot.config(xlabel='n')
thinkplot.subplot(2)
thinkplot.plot(n, n**2, label='n**2', linewidth=1, color='b')
thinkplot.plot(n, n * np.log(n), label='n*log(n)', linewidth=1, color='g')
thinkplot.config(xlabel='n')
thinkplot.subplot(3)
thinkplot.plot(n, n, label='n', linewidth=1, color='r')
thinkplot.plot(n, np.log(n), label='log(n)', linewidth=1, color='b')
thinkplot.config(xlabel='n')
thinkplot.show()
