def plot_spectrogram(wave, seg_length):
"""
"""
spectrogram = wave.make_spectrogram(seg_length)
print('Time resolution (s)', spectrogram.time_res)
print('Frequency resolution (Hz)', spectrogram.freq_res)
spectrogram.plot(high=700)
decorate(xlabel='Time(s)', ylabel='Frequency (Hz)')
def test_spectrum():
signal = Chirp(start=220, end=440)
wave = signal.make_wave(duration=1)
spectrum = wave.make_spectrum()
spectrum.plot(high=700)
decorate(xlabel='Frequency (Hz)')
signal = Chirp(start=220, end=440)
wave = signal.make_wave(duration=1, framerate=11025)
plot_spectrogram(wave, 512)
def test_Sawtooth():
signal = SawtoothSignal(200)
duration = signal.period * 3
segment = signal.make_wave(duration, framerate=10000)
segment.plot()
decorate(xlabel='Time (s)')
wave = signal.make_wave(duration=0.5, framerate=10000)
wave.apodize()
spectrum = wave.make_spectrum()
spectrum.plot()
decorate(xlabel='Frequency (Hz)')
def test_Chirp():
pathdir_out = "chap3_out"
if not os.path.exists(pathdir_out):
try:
os.makedirs(pathdir_out)
except:
pass
wavfilename = pathdir_out + "/Chirp.wav"
signal = Chirp(start=220, end=880)
wave1 = signal.make_wave(duration=2)
wave1.segment(start=0, duration=0.05).plot()
decorate(xlabel='Time (s)')
wave1.write(wavfilename)
def filter_wave(wave, start, duration, cutoff):
"""Selects a segment from the wave and filters it.
Plots the spectrum and displays an Audio widget.
wave: Wave object
start: time in s
duration: time in s
cutoff: frequency in Hz
"""
segment = wave.segment(start, duration)
spectrum = segment.make_spectrum()
spectrum.plot(high=5000, color='0.7')
spectrum.low_pass(cutoff)
spectrum.plot(high=5000, color='#045a8d')
decorate(xlabel='Frequency (Hz)')
audio = spectrum.make_wave().make_audio()
display(audio)
from thinkdsp import CosSignal, SinSignal
from thinkdsp import decorate
cos_sig = CosSignal(freq=440, amp=1.0, offset=0)
sin_sig = SinSignal(freq=880, amp=0.5, offset=0)
oadd = SinSignal(freq=500, amp=0.7, offset=0)
mix = sin_sig + cos_sig + oadd
cos_sig.plot()
decorate(xlabel='cos_sig')
sin_sig.plot()
decorate(xlabel='sin_sig')
mix.plot()
decorate(xlabel='mix')
wave = mix.make_wave(duration=5, start=0, framerate=11025)
wave.play('temp.wav')
spectrum = wave.make_spectrum()
spectrum.plot()
decorate(xlabel='Frequency (Hz)')
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()
sys.path.insert(1, 'dsp-modulo')
import numpy as np
import thinkplot as pl
from thinkdsp import decorate
from thinkdsp import UncorrelatedUniformNoise
senal = UncorrelatedUniformNoise()
wave = senal.make_wave(duration=0.5, framerate=22050)
wave.write("ruidoNoCorrelacionadoUniforme.wav")
segmento = wave.segment(duration=0.05)
segmento.plot()
decorate(xlabel="tiempo", ylabel="amplitud")
pl.show()
espectro = wave.make_spectrum()
espectro.plot_power()
decorate(xlabel="frecuencia", ylabel="power")
pl.show()
espectro_integrado = espectro.make_integrated_spectrum()
espectro_integrado.plot_power()
decorate(xlabel="frecuencia", ylabel="poder acumulado")
pl.show()
pendiente = espectro.estimate_slope()
print("pendiente: " + str(pendiente.slope))
import sys
sys.path.insert(1, 'dsp-modulo')
import numpy as np
import thinkplot as plt
from thinkdsp import decorate
from thinkdsp import PinkNoise
pendientes = [0.0, 1.5, 2.0]
for pendiente in pendientes:
senal = PinkNoise(beta=pendiente)
wave = senal.make_wave(duration=0.5, framerate=22050)
#wave.write("ruido_rosa.wav")
#wave.plot()
#decorate(xlabel="Tiempo", ylabel= "Amplitud")
#plt.show()
etiqueta = f'pendiente= {pendiente}'
espectro = wave.make_spectrum()
espectro.plot_power(label=etiqueta, alpha=0.5)
loglog = dict(xscale="log", yscale="log")
decorate(xlabel="Frecuencia", ylabel="Poder", **loglog)
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 Spectrum, TriangleSignal, SquareSignal from thinkdsp import decorate import matplotlib.pyplot as plt import numpy as np triangle = TriangleSignal(440).make_wave(duration=0.01) plt.subplot(2, 1, 1) triangle.plot() decorate(xlabel="time(s)") spectrum = triangle.make_spectrum() print(spectrum.hs[0]) spectrum.hs[0] = 100 plt.subplot(2, 1, 2) triangle.plot(color="gray") spectrum.make_wave().plot() decorate(xlabel='Time(s)') 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 decorate import thinkplot frecuencia1 = SinSignal(freq=1500, amp=0.3, offset=0) frecuencia2 = SinSignal(freq=380, amp=0.6, offset=0) frecuencia3 = SinSignal(freq=5300, amp=1, offset=0) frecuencia4 = SinSignal(freq=12300, amp=0.1, offset=0) resultante1 = frecuencia1 + frecuencia2 resultante2 = frecuencia3 + frecuencia4 waveResultante1 = resultante1.make_wave(duration=1, start=0, framerate=44100) waveResultante2 = resultante2.make_wave(duration=1, start=1.3, framerate=44100) wavefinal = waveResultante1 + waveResultante2 wavefinal.plot() decorate(xlabel="Tiempo (s)") thinkplot.show() espectro = wavefinal.make_spectrum() espectro.plot() decorate(xlabel="Hz") thinkplot.show()
from thinkdsp import Spectrum, TriangleSignal from thinkdsp import decorate import matplotlib.pyplot as plt import numpy as np signal = TriangleSignal(440) #绘制三角波 duration = signal.period*3 segment = signal.make_wave(duration, framerate=10000) plt.subplot(3,1,1) segment.plot() decorate(xlabel='Time (s)') wave = signal.make_wave(duration=0.01, framerate=10000) plt.subplot(3,1,2) Spectrum = wave.make_spectrum() Spectrum.plot() print(Spectrum.hs[0]) decorate(title=Spectrum.hs[0]) plt.subplot(3,1,3) Spectrum.hs[0] = 100 Spectrum.plot() decorate(title=Spectrum.hs[0]) plt.show()
import sys sys.path.insert(1, 'dsp-modulo') from thinkdsp import SinSignal from thinkdsp import decorate import thinkplot frecuencia1 = SinSignal(freq=1500, amp=0.3, offset=0) frecuencia2 = SinSignal(freq=380, amp=0.6, offset=0) frecuencia3 = SinSignal(freq=5300, amp=1.0, offset=0) frecuencia4 = SinSignal(freq=12300, amp=0.1, offset=0) resultante1 = frecuencia1 + frecuencia2 resultante2 = frecuencia3 + frecuencia4 waveResultante1 = resultante1.make_wave(duration=1, start=0, framerate=44100) waveResultante2 = resultante2.make_wave(duration=1, start=1.3, framerate=44100) waveFinal = waveResultante1 + waveResultante2 waveFinal.plot() decorate(xlabel="Tiempo (s)") thinkplot.show() espectro = waveFinal.make_spectrum() espectro.plot() decorate(xlabel="Fracuencia (Hz)") thinkplot.show()
import sys
sys.path.insert(1, 'dsp-modulo')
from thinkdsp import SinSignal
from thinkdsp import decorate
from thinkdsp import read_wave
import thinkplot
waveTelefono = read_wave("telefono.wav")
waveTelefono.plot()
decorate(xlabel="Tiempo(s)")
thinkplot.show()
#espectro = waveTelefono.make_spectrum()
#espectro.plot()
#decorate(xlabel='Frecuencia (Hz)')
#thinkplot.show()
wavePrimerDigito = waveTelefono.segment(start=0, duration=0.5)
wavePrimerDigito.plot()
decorate(xlabel="Tiempo (s)")
thinkplot.show()
#2
espectroPrimerDigito = wavePrimerDigito.make_spectrum()
#espectroPrimerDigito.plot()
#decorate(xlabel='Frecuencia (Hz)')
#thinkplot.show()
import sys sys.path.insert(1, 'dsp-modulo') from thinkdsp import SinSignal from thinkdsp import decorate import thinkplot frecuencia1 = SinSignal(freq=1500, amp=0.3, offset=0) frecuencia2 = SinSignal(freq=380, amp=0.6, offset=0) frecuencia3 = SinSignal(freq=5300, amp=1.0, offset=0) frecuencia4 = SinSignal(freq=12300, amp=0.1, offset=0) resultante1 = frecuencia1 + frecuencia2 resultante2 = frecuencia3 + frecuencia4 waveResultante1 = resultante1.make_wave(duration=1, start=0, framerate=44100) waveResultante2 = resultante2.make_wave(duration=1, start=1.3, framerate=44100) waveFinal = waveResultante1 + waveResultante2 waveFinal.plot() decorate(xlabel="tiempo S") thinkplot.show() espectro = waveFinal.make_spectrum() espectro.plot() decorate(xlabel="frecuencia Hz") thinkplot.show()
#decorate(xlabel="Tiempo (s)") #thinkplot.show() #espectro = waveTelefono.make_spectrum() #espectro.plot() #decorate(xlabel="Frecuencia (Hz)") #thinkplot.show wavePrimerDigito = waveTelefono.segment(start=0, duration=0.5) #wavePrimerDigito.plot() #decorate(xlabel="Tiempo (s)") #thinkplot.show() # 22-45-32 espectroPrimerDigito = wavePrimerDigito.make_spectrum() espectroPrimerDigito.plot() decorate(xlabel="Frecuencia 1 (Hz)") thinkplot.show() waveSegundoDigito = waveTelefono.segment(start=0.5, duration=0.5) espectroSegundoDigito = waveSegundoDigito.make_spectrum() espectroSegundoDigito.plot() decorate(xlabel="Frecuencia 2 (Hz)") thinkplot.show() waveTercerDigito = waveTelefono.segment(start=1, duration=0.5) espectroTercerDigito = waveTercerDigito.make_spectrum() espectroTercerDigito.plot() decorate(xlabel="Frecuencia 3 (Hz)") thinkplot.show() waveCuartoDigito = waveTelefono.segment(start=1.5, duration=0.5)
import sys
sys.path.insert(1, 'dsp-modulo')
import numpy as np
import thinkplot as plt
from thinkdsp import decorate
from thinkdsp import BrownianNoise
senal = BrownianNoise()
wave = senal.make_wave(duration=0.5, framerate=22050)
wave.write("ruidoBrowniano.wav")
wave.plot()
decorate(xlabel="Tiempo", ylabel="Amplitud")
plt.show()
espectro = wave.make_spectrum()
espectro.plot_power()
loglog = dict(xscale="log", yscale="log")
decorate(xlabel="frecuencia", ylabel="poder", **loglog)
plt.show()
pendiente = espectro.estimate_slope()
print("pendiente" + str(pendiente.slope))
import thinkdsp
import numpy as np
from thinkdsp import Chirp, SawtoothSignal, Sinusoid
import math
import matplotlib.pyplot as plt
from winsound import PlaySound
wave = thinkdsp.read_wave('72475__rockwehrmann__glissup02.wav')
wave.make_spectrogram(512).plot(high=5000)
thinkdsp.decorate(xlabel='Time (s)', ylabel='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)', ylabel='Amplitud') waveSeno.plot() waveCoseno.plot() plt.show() decorate(xlabel="Tiempo (s)") decorate(ylabel="Amplitud") waveResultante.plot() plt.show()
"""
改写evaluate函数
ts: 时间
"""
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 = Chirp(start=220, end=440)
wave = signal.make_wave(duration=1)
spectrum = wave.make_spectrum()
plt.subplot(2, 1, 1)
spectrum.plot(high=700)
decorate(xlabel='Frequency (Hz)')
wave.play("niaojiao.wav")
signal = SawtoothChirp(start=220, end=880)
wave = signal.make_wave(duration=1, framerate=14000)
sp = wave.make_spectrogram(256)
plt.subplot(2, 1, 2)
sp.plot()
decorate(xlabel='Time (s)', ylabel='Frequency (Hz)')
plt.show()
#wave.play("temp2.wav")
from thinkdsp import SawtoothSignal, Signal, Spectrum import matplotlib.pyplot as plt from thinkdsp import decorate Signal = SawtoothSignal(200) duration = Signal.period * 3 segment = Signal.make_wave(duration, framerate=20000) segment.plot() decorate(xlabel='Time(s)') plt.show() plt.show() wave = Signal.make_wave(duration=0.5, framerate=10000) wave.apodize() wave.make_audio() wave.write(filename='2-2.wav') Spectrum = wave.make_spectrum() Spectrum.plot() decorate(xlabel='频谱(Hz)') plt.show()
import sys
sys.path.insert(1, 'dsp-modulo')
import numpy as np
import thinkplot as plt
from thinkdsp import decorate
from thinkdsp import UncorrelatedUniformNoise
senal = UncorrelatedUniformNoise()
wave = senal.make_wave(duration=0.5, framerate=22050)
wave.write("ruido_no_correlacional_uniforme.wav")
segmento = wave.segment(duration=0.05)
segmento.plot()
decorate(xlabel="Tiempo(s)", ylabel="Amplitud")
plt.show()
espectro = wave.make_spectrum()
espectro.plot_power()
decorate(xlabel="Frecuencia (Hz)", ylabel="Poder")
plt.show()
espectro_integrado = espectro.make_integrated_spectrum()
espectro_integrado.plot_power()
decorate(xlabel="Frecuencia (Hz)", ylabel="Poder acumulado")
plt.show()
pendiente = espectro.estimate_slope()
print("Pendiente: " + str(pendiente.slope))
import os
import wget
import matplotlib.pyplot as plt
from converter import fromMp3ToWav
from matrix_creator import VolumeMatrix
from constellation_map_creator import ConstellationMap
if not os.path.exists('thinkdsp.py'):
wget.download(
'https://github.com/AllenDowney/ThinkDSP/raw/master/code/thinkdsp.py')
from thinkdsp import read_wave, decorate # no pep8
if __name__ == "__main__":
src = '~PATH_TO_THE_SOUND_SOURCE/[file_name.mp3 or file_name.wav]'
if 'mp3' in src:
src = fromMp3ToWav(src)
wave = read_wave(src)
wave.normalize()
matrix = VolumeMatrix(wave, (200, 2000), 0.01)
matrix.decorator()
const_map = ConstellationMap(matrix)
const_map.find_stars()
stars = const_map.data_for_map_drawing
plt.figure(figsize=(10, 7))
plt.subplots_adjust(bottom=0.1)
plt.scatter(stars[:, 0], stars[:, 1], marker="x")
decorate(xlabel='Time, s', ylabel='Frequency, Hz')
plt.show()
from thinkdsp import SinSignal
from thinkdsp import decorate
from thinkdsp import read_wave
from thinkdsp import play_wave
import matplotlib.pyplot as plt
seno = SinSignal(freq=440, amp=1.0, offset=0)
segundo_seno = SinSignal(freq=340, amp=1, offset=0)
tercer_seno = SinSignal(freq=600, amp=0.7, offset=0)
wave_seno = seno.make_wave(duration=1.0, start=1, framerate=44100)
wave_segundo_seno = segundo_seno.make_wave(duration=1.0,
start=2,
framerate=44100)
wave_tercer_seno = tercer_seno.make_wave(duration=1.0,
start=3,
framerate=44100)
resultante = wave_seno + wave_segundo_seno + wave_tercer_seno
decorate(xLabel="Tiempo (s)")
decorate(yLabel="Amplitud")
resultante.plot()
resultante.write("Sonido.wav")
plt.show()
import sys sys.path.insert(1, 'dsp-modulo') from thinkdsp import SinSignal from thinkdsp import decorate from thinkdsp import CosSignal #crear señal senoidal seno = SinSignal(freq=400, amp=0.7, offset=0) coseno = CosSignal(freq=800, amp=1.1, offset=0) #modulo para mostrar grafiicas import matplotlib.pyplot as plt #crear grafica en memoria seno.plot() decorate(xlabel='tiempo (s)') decorate(ylabel='amplitud') coseno.plot() plt.show()
import sys sys.path.insert(1, 'dsp-modulo') from thinkdsp import SinSignal from thinkdsp import decorate import thinkplot frecuencia1 = SinSignal(freq=1500, amp=0.3, offset=0) frecuencia2 = SinSignal(freq=380, amp=0.6, offset=0) frecuencia3 = SinSignal(freq=5300, amp=1.0, offset=0) frecuencia4 = SinSignal(freq=12300, amp=0.1, offset=0) resultante1 = frecuencia1 + frecuencia2 resultante2 = frecuencia3 + frecuencia4 waveResultante1 = resultante1.make_wave(duration=1,start=0,framerate=44100) waveResultante2 = resultante2.make_wave(duration=6,start=1.3,framerate=44100) waveFinal = waveResultante1 + waveResultante2 waveFinal.plot() decorate(xLabel="Tiempo (s)") thinkplot.show() espectro = waveFinal.make_spectrum() espectro.plot() decorate(xLabel="Frecuencia (Hz)") thinkplot.show()
import sys
sys.path.insert(1,'dsp-modulo')
import numpy as np
import thinkplot as plt
from thinkdsp import decorate
from thinkdsp import PinkNoise
pendientes = [0.0, 1.5, 2.0]
for pendiente in pendientes:
senal = PinkNoise(beta=pendiente)
wave = senal.make_wave(duration=0.5, framerate=22050)
#wave.write("ruidorosa.wav")
#wave.plot()
#decorate(xlabel="tiempo",ylabel="amplitud")
#plt.show()
etiqueta = f'pendiente={pendiente}'
#etiqueta = "pendiente=" + pendiente
espectro = wave.make_spectrum()
espectro.plot_power()
loglog = dict(xscale="log",yscale="log")
decorate(xlabel="frecuencia", ylabel="poder", **loglog)
plt.show()