from thinkdsp import CosSignal, SinSignal
from thinkdsp import decorate
import matplotlib.pyplot as plt
cos_sig = CosSignal(freq=440, amp=1.0, offset=0)
sin_sig = SinSignal(freq=880, amp=0.5, offset=0)
mix = sin_sig + cos_sig
wave = mix.make_wave(duration=0.01, start=0, framerate=11025)
wave.play('test3.wav')
wave.normalize()
wave.make_audio()
plt.subplot(2, 1, 1)
wave.plot()
spectrum = wave.make_spectrum()
plt.subplot(2, 1, 2)
spectrum.plot(high=5000)
decorate(xlabel='Frequency (Hz)')
plt.show()
#import sys #sys.path.insert(1,'dsp-modulo') from thinkdsp import SinSignal from thinkdsp import CosSignal from thinkdsp import decorate #modulo para mostrar las graficas import matplotlib.pyplot as plt #crear señal senoidal seno = SinSignal(freq=200, amp=0.7, offset=0) coseno = CosSignal(freq=800, amp=1.1, offset=0) #creamos grafica y asignamos propiedades seno.plot() coseno.plot() decorate(xlabel='Tiempo (s)') decorate(ylabel='Amplitud') plt.show()
import sys sys.path.insert(1, 'dsp-modulo') from thinkdsp import SinSignal from thinkdsp import CosSignal from thinkdsp import decorate import matplotlib.pyplot as plt seno = SinSignal(freq=20, amp=1, offset=0) coseno = CosSignal(freq=50, amp=1.3, offset=0) waveSeno = seno.make_wave(duration=1, start=0, framerate=11025) waveCoseno = coseno.make_wave(duration=1, start=0, framerate=11025) waveResultante = waveSeno + waveCoseno decorate(xlabel="Tiempo (s)") decorate(ylabel="Amplitud") waveSeno.plot() waveCoseno.plot() plt.show() decorate(xlabel="Tiempo (s)") decorate(ylabel="Amplitud") waveResultante.plot() plt.show()
from thinkdsp import CosSignal, SinSignal, decorate
import matplotlib.pyplot as plt
cosine_signal = CosSignal(freq=440, amp=1.0, offset=0)
sine_signal = SinSignal(freq=880, amp=0.5, offset=0)
cosine_signal.plot()
decorate(xlabel='Time (s)')
# figure, (axes1, axes2) = plt.subplots(nrows=2)
# axes1.plot(cosine_signal)
# axes1.set_xlabel('Time (s)')
plt.show()
import sys sys.path.insert(1, 'dsp-modulo') from thinkdsp import SinSignal from thinkdsp import CosSignal from thinkdsp import decorate #Módulo para graficar import matplotlib.pyplot as plt #Crear señal senoidal seno = SinSignal(freq=329.628, amp=50, offset=0) coseno = CosSignal(freq=41.2035, amp=30, offset=0) #Crear gráfica en memoria y damos propiedades seno.plot() decorate(xlabel='Tiempo (s)') decorate(ylabel='Amplitud') coseno.plot() plt.show()
from thinkdsp import CosSignal, SinSignal from thinkdsp import decorate cos_sig = CosSignal(freq=440, amp=1, offset=0) sin_sig = SinSignal(freq=880, amp=0.5, offset=0) cos_sig.plot() decorate(xlabel='Time (s)')
import os
if not os.path.exists('thinkdsp.py'):
get_ipython().system(
'wget https://github.com/AllenDowney/ThinkDSP/raw/master/code/thinkdsp.py'
)
# ## Signals
#
# Instantiate cosine and sine signals.
# In[33]:
from thinkdsp import CosSignal, SinSignal
cos_sig = CosSignal(freq=450, amp=1.0, offset=0)
sin_sig = SinSignal(freq=900, amp=0.5, offset=0)
# Plot the sine and cosine signals. By default, `plot` plots three periods.
# In[34]:
from thinkdsp import decorate
cos_sig.plot()
decorate(xlabel='Time (s)')
# Here's the sine signal.
# In[35]:
import matplotlib.pyplot as plt from thinkdsp import TriangleSignal, decorate, SquareSignal, SawtoothSignal, CosSignal signal = CosSignal(4500) duration = signal.period * 5 segment = signal.make_wave(duration, framerate=10000) plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axes.unicode_minus'] = False decorate(xlabel='Time (s)') plt.subplot(121) segment.plot() signal = CosSignal(5500) duration = signal.period * 5 segment = signal.make_wave(duration, framerate=10000) decorate(xlabel='Frequency (Hz)') plt.subplot(122) segment.plot() plt.show()
import os
import librosa
import numpy as np
from scipy.io.wavfile import write
from thinkdsp import read_wave, CosSignal
wave = read_wave('105977__wcfl10__favorite-station.wav')
carrier_sig = CosSignal(freq=440)
carrier_wave = carrier_sig.make_wave(duration=wave.duration,
framerate=wave.framerate)
modulated = wave * carrier_wave
# amplitude modulation - multiplying the input wave by a carrier wave in the time domain
modulated.make_audio()
modulated.play('out1.wav')
y, sr = librosa.load(
'105977__wcfl10__favorite-station.wav',
sr=44100) # y is a numpy array of the wav file, sr = sample rate
y_shifted = librosa.effects.pitch_shift(y, sr,
n_steps=-8) # shifted by n_steps
# pitch shift - a step is equal to a semitone
write('out2.wav', 44100, y_shifted)
print('Writing out2.wav')
#combining amplitude modulation and pitch shift together for greater voice modulation
y, sr = librosa.load('out1.wav', sr=44100)
y_shifted = librosa.effects.pitch_shift(y, sr, n_steps=-8)
write('out1_2.wav', 44100, y_shifted)
plt.show() segment.segment(start=1.1, duration=0.005).plot() spectrum = segment.make_spectrum() spectrum.plot(high=7000) plt.show() spectrum.low_pass(4000) spectrum.plot(high=7000) plt.show() spectrum.high_pass(1000) spectrum.plot(high=7000) plt.show() spectrum.band_stop(2500, 1000) spectrum.plot(high=7000) plt.show() cos_sig = CosSignal(freq=440, amp=1.0, offset=0) sin_sig = SinSignal(freq=880, amp=2.0, offset=0) # # 正弦信号和波形 plt.subplot() cos_sig.plot() decorate(xlabel='Time (s)') wave1 = cos_sig.make_wave(duration=1) wave1.apodize() wave1.make_audio() spectrum1 = wave1.make_spectrum() plt.subplot() spectrum1.plot(high=2000) # # 余弦信号和波形 sin_sig.plot()
