def main():
numpy.set_printoptions(precision=3, suppress=True)
test_dct()
return
synthesize_example()
return
test_synthesize(fshift=0, tshift=0)
test_synthesize(fshift=0.5, tshift=0.5)
return
cos_sig = thinkdsp.CosSignal(freq=1)
wave = cos_sig.make_wave(duration=1, start=0, framerate=4)
print wave.ys
dct = scipy.fftpack.dct(wave.ys, type=2)
print dct
cos_trans = wave.cos_transform()
xs, ys = zip(*cos_trans)
print ys
return
framerate = 4000
cos_sig = (thinkdsp.CosSignal(freq=440) + thinkdsp.SinSignal(freq=660) +
thinkdsp.CosSignal(freq=880))
wave = cos_sig.make_wave(duration=0.5, start=0, framerate=framerate)
res = wave.cos_transform()
for index in range(3):
plot(res, index)
def step_4():
Sin1 = thinkdsp.CosSignal(freq=261.63, amp=0.5, offset=0)
Sin2 = thinkdsp.CosSignal(freq=329.63, amp=0.5, offset=0)
Sin3 = thinkdsp.CosSignal(freq=392.0, amp=0.5, offset=0)
SumSignal = Sin1 + Sin2 + Sin3
SumSignal_wave = SumSignal.make_wave(duration=3, start=0, framerate=8000)
period = SumSignal.period
SumSignal_seg = SumSignal_wave.segment(start=0, duration=period * 5)
SumSignal_seg.plot()
tp.show()
SumSignal_wave.write(filename='output.wav')
def main():
# test signal for proof of concept
sig1 = thinkdsp.CosSignal(freq=20, amp=1.0)
sig2 = thinkdsp.CosSignal(freq=2500, amp=0.05)
sig3 = thinkdsp.CosSignal(freq=3000, amp=0.04)
sig4 = thinkdsp.CosSignal(freq=3500, amp=0.03)
sig = sig1 + sig2 + sig3 + sig4
# set sampling frequency
framerate = 20000
# make a wave object from signal object
wave = sig.make_wave(duration=1, start=0, framerate=framerate)
demodulate_steps(wave=wave)
def mix_cosines():
"""Plots three periods of a mix of cosines.
"""
# create a SumSignal
cos_sig = thinkdsp.CosSignal(freq=440, amp=1.0, offset=0)
sin_sig = thinkdsp.SinSignal(freq=880, amp=0.5, offset=0)
mix = sin_sig + cos_sig
# create a wave
wave = mix.make_wave(duration=1.0, start=0, framerate=11025)
print('Number of samples', len(wave))
print('Timestep in ms', 1000 / wave.framerate)
assert len(wave) == wave.framerate
# select a segment
period = mix.period
segment = wave.segment(start=0, duration=period * 3)
# plot the segment
thinkplot.preplot(1)
segment.plot()
thinkplot.Save(root='sounds4',
xlabel='Time (s)',
axis=[0, period * 3, -1.55, 1.55],
formats=FORMATS,
legend=False)
def broadcast(src_path, tag):
#files are sourced and saved from/to the same path
#normalizes amplitude
os.chdir(src_path)
for file in os.listdir(src_path):
if file.endswith('.wav'):
wave = td.read_wave(src_path + file)
carrier_sig = td.CosSignal(freq=10000)
carrier_wave = carrier_sig.make_wave(duration=wave.duration,
framerate=wave.framerate)
modulated = wave * carrier_wave
demodulated = modulated * carrier_wave
demodulated_spectrum = demodulated.make_spectrum(full=True)
demodulated_spectrum.low_pass(10000)
filtered = demodulated_spectrum.make_wave()
filtered.write(filename='BC_' + file)
#create json file if there is no existing json file provided
if tag is not None:
if file.endswith('.wav'):
json_file_name = re.sub("\.wav", ".json", file)
data = {'tags': [tag]}
with open(src_path + 'BC_' + json_file_name,
'w') as outfile:
json.dump(data, outfile)
#copy json file if is provided
elif tag is None:
if file.endswith('.json'):
shutil.copyfile(src_path + file, src_path + 'BC_' + file)
def mix_cosines():
"""Demonstrates methods in the thinkdsp module.
"""
# create a SumSignal
cos_sig = thinkdsp.CosSignal(freq=440, amp=1.0, offset=0)
sin_sig = thinkdsp.SinSignal(freq=880, amp=0.5, offset=0)
mix = sin_sig + cos_sig
# create a wave
wave = mix.make_wave(duration=0.5, start=0, framerate=11025)
print 'Number of samples', len(wave.ys)
print 'Timestep in ms', 1.0 / 11025 * 1000
# select a segment
period = mix.period
segment = wave.segment(start=0, duration=period*3)
# plot the segment
segment.plot()
thinkplot.Save(root='example1',
xlabel='time (s)',
axis=[0, period*3, -1.55, 1.55])
# write the whole wave
wave.normalize()
wave.apodize()
wave.write(filename='example1.wav')
# play the wave
thinkdsp.play_wave(filename='example1.wav', player='aplay')
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)
def test2():
cos_sig = thinkdsp.CosSignal(freq=440, amp=1.0, offset=0)
sin_sig = thinkdsp.SinSignal(freq=800, amp=0.5, offset=0)
mix = cos_sig + sin_sig
wave = mix.make_wave(duration=2, start=0, framerate=16000)
wave.normalize() # 归一化
wave.write(filename='play3.wav')
wave.apodize() # 渐入渐出
wave.write(filename='play4.wav')
def aliasing_example():
framerate = 10000
thinkplot.preplot(num=2)
freq1 = 4500
signal = thinkdsp.CosSignal(freq1)
duration = signal.period*5
segment = signal.make_wave(duration, framerate=framerate)
segment.plot(label=freq1)
freq2 = 5500
signal = thinkdsp.CosSignal(freq2)
#duration = signal.period*10
segment = signal.make_wave(duration, framerate=framerate)
segment.plot(label=freq2)
thinkplot.save(root='aliasing-3',
xlabel='time (s)',
axis=[0, duration, -1.05, 1.05]
)
def my_gen_bpsk_1(bits, sample_rate=8000, symbol_period=.01, freq=1000):
symbol_len = symbol_period * sample_rate
square_signal = bits_to_signal(bits, symbol_len)
transmission_duration = len(square_signal) * symbol_period
cos_signal = thinkdsp.CosSignal(freq=freq, offset=0)
print transmission_duration
print sample_rate
cos_wave = cos_signal.make_wave(duration=transmission_duration,
framerate=sample_rate)
print cos_wave
print square_signal
print len(cos_wave.ys)
print len(square_signal)
return np.multiply(cos_wave.ys, square_signal)
def synthesize1(amps, fs, ts):
"""Synthesize a mixture of cosines with given amps and fs.
amps: amplitudes
fs: frequencies in Hz
ts: times to evaluate the signal
returns: wave array
"""
components = [thinkdsp.CosSignal(freq, amp) for amp, freq in zip(amps, fs)]
signal = thinkdsp.SumSignal(*components)
ys = signal.evaluate(ts)
return ys
def signal(offset):
cos_sig = thinkdsp.CosSignal(freq=1.0, amp=1.0, offset=offset)
sin_sig = thinkdsp.SinSignal(freq=1.0, amp=1.0, offset=offset)
cos_wave = cos_sig.make_wave(duration=0.5, start=0, framerate=8000)
sin_wave = sin_sig.make_wave(duration=0.5, start=0, framerate=8000)
period = sin_sig.period
cos_seg = cos_wave.segment(start=0, duration=period * 5)
sin_seg = sin_wave.segment(start=0, duration=period * 5)
sin_seg.plot()
tp.show()
cos_seg.plot()
tp.show()
def aliasing_example(offset=0.000003):
"""Makes a figure showing the effect of aliasing.
"""
framerate = 10000
thinkplot.preplot(num=2)
freq1 = 4500
signal = thinkdsp.CosSignal(freq1)
duration = signal.period * 5
segment = signal.make_wave(duration, framerate=framerate)
thinkplot.Hlines(0, 0, duration, color='gray')
segment.shift(-offset)
segment.plot_vlines(label=freq1, linewidth=3)
freq2 = 5500
signal = thinkdsp.CosSignal(freq2)
segment = signal.make_wave(duration, framerate=framerate)
segment.shift(+offset)
segment.plot_vlines(label=freq2, linewidth=3)
thinkplot.save(root='aliasing1',
xlabel='Time (s)',
axis=[-0.00002, duration, -1.05, 1.05])
def test1():
cos_sig = thinkdsp.CosSignal(freq=440, amp=1.0, offset=0)
sin_sig = thinkdsp.SinSignal(freq=880, amp=0.5, offset=0)
mix = cos_sig + sin_sig
wave = mix.make_wave(duration=10, start=0, framerate=16000)
wave.normalize() # 归一化
wave.apodize() # 渐入渐出
wave.plot()
plt.show()
wave.write(filename='output.wav')
# 显示原波形
violin_wave = thinkdsp.read_wave('output.wav')
segment = violin_wave.segment(start=0, duration=2 / 440)
segment.plot()
plt.show()
# 频谱
spectrum = violin_wave.make_spectrum()
spectrum.plot()
plt.show()
# 低通
spectrumlow = spectrum.copy()
spectrumlow.low_pass(cutoff=600, factor=0.01)
spectrumlow.plot()
plt.show()
violin_wave = spectrumlow.make_wave()
segment = violin_wave.segment(start=0, duration=2 / 440)
segment.plot()
plt.show()
# 高通
spectrumhigh = spectrum.copy()
spectrumhigh.high_pass(cutoff=600, factor=0.01)
spectrumhigh.plot()
plt.show()
violin_wave = spectrumhigh.make_wave()
segment = violin_wave.segment(start=0, duration=2 / 440)
segment.plot()
plt.show()
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 testDct(self):
signal = thinkdsp.CosSignal(freq=2)
wave = signal.make_wave(duration=1, framerate=8)
dct = wave.make_dct()
self.assertAlmostEqual(dct.fs[0], 0.25)
def synthesize1(amps, fs, ts):
components = [thinkdsp.CosSignal(freq, amp) for amp, freq in zip(amps, fs)]
signal = thinkdsp.SumSignal(*components)
ys = signal.evaluate(ts)
return ys
from ipywidgets import interact, interactive, fixed
import ipywidgets as widgets
from IPython.display import display
from matplotlib import pyplot
def stretch(wave, stretch_factor):
return thinkdsp.Wave(wave.ys,
wave.ts / stretch_factor,
framerate=wave.framerate * stretch_factor)
start_time = datetime.datetime.now()
cos_sig = thinkdsp.CosSignal(freq=440, amp=1.0, offset=0)
sin_sig = thinkdsp.CosSignal(freq=1000, amp=0.5, offset=0)
mix = sin_sig + cos_sig
wave = mix.make_wave(duration=0.5, start=0, framerate=10000)
period = mix.period
segment = wave.segment(start=0, duration=period * 3)
segment.plot()
thinkplot.show()
mix_spectrum = wave.make_spectrum()
mix_spectrum.plot()
# plt.show() # # wave1 = signal1.make_wave(duration=0.5, framerate=10000) # spectrum1 = wave1.make_spectrum() # spectrum1.plot() # plt.show() # # ''' square signal analysis''' # signal2= thinkdsp.SquareSignal(100) # signal2.plot() # plt.show() # # wave2 = signal2.make_wave(duration=0.5, framerate=10000) # spectrum2 = wave2.make_spectrum() # spectrum2.plot() # plt.show() ''' aliasing analysis''' framerate = 10000 signal = thinkdsp.CosSignal(4500) duration = signal.period*5 segment = signal.make_wave(duration, framerate=framerate) segment.plot() plt.show() signal = thinkdsp.CosSignal(5500) segment = signal.make_wave(duration, framerate=framerate) segment.plot() plt.show()
# create a subplot ax = fig.add_subplot(223) # plot a wave new_wave.plot(label='new wave', color='b') ax.legend() # create a subplot ax = fig.add_subplot(224) # plot a spectrum new_spectrum.plot(label='new spec', color='b') ax.legend() plt.show() ''' # testing integration sig = thinkdsp.CosSignal(freq=1, amp=1, offset=0) wave = sig.make_wave(duration=1, start=0, framerate=100) spectrum = wave.make_spectrum() new_spectrum = spectrum.integrate() new_wave = new_spectrum.make_wave() # create a figure fig = plt.figure() # create a subplot ax = fig.add_subplot(221) # plot a wave wave.plot(label='wave', color='b') ax.legend() # create a subplot ax = fig.add_subplot(222) # plot a spectrum
import thinkdsp import matplotlib.pyplot as plt cos_signal = thinkdsp.CosSignal(freq=440, amp=1.0, offset=0) sin_sigal = thinkdsp.SinSignal(freq=880, amp=0.5, offset=0) mix = sin_sigal + cos_signal wave = mix.make_wave(duration=0.5, start=0, framerate=11025) wave.plot() plt.show()
import thinkdsp import thinkplot import numpy cos_sig = thinkdsp.CosSignal(freq=440) cos_sig.plot() thinkplot.config(xlabel='time', legend=False)
#%matplotlib inline import thinkdsp import thinkplot import numpy as np from ipywidgets import interact, interactive, fixed import ipywidgets as widgets from IPython.display import display # Instantiate cosine and sine signals. # In[2]: cos_sig = thinkdsp.CosSignal(freq=440, amp=1.0, offset=0) sin_sig = thinkdsp.SinSignal(freq=880, amp=0.5, offset=0) # Plot the sine and cosine signals. By default, `plot` plots three periods. # In[3]: cos_sig.plot() thinkplot.config(xlabel='Time (s)') # Notice that the frequency of the sine signal is doubled, so the period is halved. # In[5]: sin_sig.plot() thinkplot.config(xlabel='Time (s)')
waveguitar.normalize() waveguitar.make_audio() waveguitar.plot() segment_guitar = waveguitar.segment(start=1.1, duration=1) segment_guitar.make_audio() segment_guitar.plot() segment_guitar.segment(start=1.1, duration=0.005).plot() spectrum_guitar = segment_guitar.make_spectrum() spectrum_guitar.plot(high=410) spectrum_guitar.low_pass(2000) spectrum_guitar.make_wave().make_audio() spectrum_guitar.peaks()[:10] cos_sig_sax = thinkdsp.CosSignal(freq=492, amp=1.0, offset=0) cos_sig_guitar = thinkdsp.CosSignal(freq=401, amp=1.0, offset=0) cos_sig = cos_sig_sax + cos_sig_guitar cos_sig.plot() thinkplot.config(xlabel='Time (s)') wave2 = cos_sig.make_wave(duration=1) wave2.apodize() wave2.make_audio()
import thinkdsp
import matplotlib.pyplot as plt
from winsound import PlaySound
plt.rcParams['font.sans-serif'] = ['KaiTi'] # 指定默认字体楷体
plt.rcParams['axes.unicode_minus'] = False # 解决保存图像是负号'-'显示为方块的问题
def play(file, flags):
print('Now play ' + file)
PlaySound(file, flags)
print('end')
sin = thinkdsp.SinSignal(freq=400, amp=1.0)
cos = thinkdsp.CosSignal(freq=1200, amp=0.8)
signal = cos + sin
plt.subplot(121)
plt.title("复合信号")
signal.plot()
wave = signal.make_wave(duration=1)
spectrum = wave.make_spectrum()
plt.subplot(122)
plt.title("复合信号频谱")
spectrum.plot(high=2000)
wave.normalize()
wave.write("复合信号.wav")
play("复合信号.wav", flags=1)
plt.show()
def get_cosine_wave(freq, offset, duration=0.1, framerate=40000):
signal = thinkdsp.CosSignal(freq=freq, amp=1.0, offset=offset)
wave = signal.make_wave(duration=duration, start=0, framerate=framerate)
return wave.ys
import os
import thinkdsp as dsp
import matplotlib.pyplot as plt
from winsound import PlaySound
plt.rcParams['font.sans-serif'] = ['KaiTi'] # 指定默认字体
plt.rcParams['axes.unicode_minus'] = False # 解决保存图像是负号'-'显示为方块的问题
def play(file, flags):
print('Now play ' + file)
PlaySound(file, flags)
print('end')
sin = dsp.SinSignal(freq=400, amp=1.0)
cos = dsp.CosSignal(freq=1000, amp=0.5)
signal = cos + sin
plt.subplot(121)
plt.title("复合信号")
signal.plot()
wave = signal.make_wave(duration=1)
spectrum = wave.make_spectrum()
plt.subplot(122)
plt.title("复合信号频谱")
spectrum.plot(high=2000)
wave.normalize()
wave.write("复合信号.wav")
play("复合信号.wav", flags=1)
plt.show()
import thinkdsp
import matplotlib.pyplot as plt
from winsound import PlaySound
plt.rcParams['font.sans-serif'] = ['KaiTi'] # 指定默认字体
plt.rcParams['axes.unicode_minus'] = False # 解决保存图像是负号'-'显示为方块的问题
def play(file, flags):
print('Now play ' + file)
PlaySound(file, flags)
print('end')
sin = thinkdsp.SinSignal(freq=400, amp=1.0)
cos = thinkdsp.CosSignal(freq=1000, amp=0.5)
signal = cos + sin
plt.subplot(121)
plt.title("复合信号")
signal.plot()
wave = signal.make_wave(duration=1)
spectrum = wave.make_spectrum()
plt.subplot(122)
plt.title("复合信号频谱")
spectrum.plot(high=2000)
wave.normalize()
wave.write("复合信号.wav")
play("复合信号.wav", flags=1)
plt.show()
import thinkdsp
import matplotlib.pyplot as pyplot
import random
pyplot.gcf().clear()
cos_sig = thinkdsp.CosSignal(5, 0.6, 0)
sin_sig = thinkdsp.SinSignal(15, 0.5, 0)
sin_sig2 = thinkdsp.SinSignal(25, 0.5, 0)
sin_sig3 = thinkdsp.SinSignal(35, 0.9, 0)
for x in range(1, 100, 1):
sin_sig3 += thinkdsp.SinSignal(x, random.uniform(0.001, 0.11), 0)
mix = cos_sig + sin_sig + sin_sig2 + sin_sig3
wave = mix.make_wave(100, 0, 11025)
print(wave.ys)
wave.plot()
pyplot.show()
period = mix.period
segment = wave.segment(0, 3 * period)
segment.plot()
spectrum = wave.make_spectrum()
spectrum.plot(high=100)
pyplot.show()
wave.write(filename='naveed.wav')
#
#pyplot.gcf().clear()
#cos_sig = thinkdsp.CosSignal(5,0.6,0)
#sin_sig = thinkdsp.SinSignal(15,0.5,0)
#sin_sig2 = thinkdsp.SinSignal(25,0.5,0)
#sin_sig3 = thinkdsp.SinSignal(35,0.5,0)
#for x in range(1,100,1):
