如何绘制一个wav文件

Question

我刚刚读了一个带scipy的wav文件,现在我想用matplotlib制作文件的图,在"y scale"上我希望看​​到aplitude和"x scale"我想看到帧的数量!任何帮助我该怎么办？谢谢!

from scipy.io.wavfile import read
import numpy as np
from numpy import*
import matplotlib.pyplot as plt
a=read("C:/Users/Martinez/Desktop/impulso.wav")
print a

Answer 1

您可以调用wave lib来读取音频文件.

要绘制波形,请使用matplotlib中的"plot"功能

import matplotlib.pyplot as plt
import numpy as np
import wave
import sys


spf = wave.open("wavfile.wav", "r")

# Extract Raw Audio from Wav File
signal = spf.readframes(-1)
signal = np.fromstring(signal, "Int16")


# If Stereo
if spf.getnchannels() == 2:
    print("Just mono files")
    sys.exit(0)

plt.figure(1)
plt.title("Signal Wave...")
plt.plot(signal)
plt.show()

你会有类似的东西:

要以秒为单位绘制x轴,你需要获得帧率并除以信号的大小,你可以使用numpy的linspace函数来创建一个与音频文件大小线性间隔的时间向量,最后你可以再次使用plot喜欢 plt.plot(Time,signal)

import matplotlib.pyplot as plt
import numpy as np
import wave
import sys


spf = wave.open("Animal_cut.wav", "r")

# Extract Raw Audio from Wav File
signal = spf.readframes(-1)
signal = np.fromstring(signal, "Int16")
fs = spf.getframerate()

# If Stereo
if spf.getnchannels() == 2:
    print("Just mono files")
    sys.exit(0)


Time = np.linspace(0, len(signal) / fs, num=len(signal))

plt.figure(1)
plt.title("Signal Wave...")
plt.plot(Time, signal)
plt.show()

以秒为单位的新绘图x轴:

Answer 2

或者,如果您想使用SciPy,您还可以执行以下操作:

from scipy.io.wavfile import read
import matplotlib.pyplot as plt

# read audio samples
input_data = read("Sample.wav")
audio = input_data[1]
# plot the first 1024 samples
plt.plot(audio[0:1024])
# label the axes
plt.ylabel("Amplitude")
plt.xlabel("Time")
# set the title  
plt.title("Sample Wav")
# display the plot
plt.show()

Answer 3

这是一个版本,它也将处理立体声输入,基于@ederwander的答案

import matplotlib.pyplot as plt
import numpy as np
import wave

file = 'test.wav'

with wave.open(file,'r') as wav_file:
    #Extract Raw Audio from Wav File
    signal = wav_file.readframes(-1)
    signal = np.fromstring(signal, 'Int16')

    #Split the data into channels 
    channels = [[] for channel in range(wav_file.getnchannels())]
    for index, datum in enumerate(signal):
        channels[index%len(channels)].append(datum)

    #Get time from indices
    fs = wav_file.getframerate()
    Time=np.linspace(0, len(signal)/len(channels)/fs, num=len(signal)/len(channels))

    #Plot
    plt.figure(1)
    plt.title('Signal Wave...')
    for channel in channels:
        plt.plot(Time,channel)
    plt.show()

Answer 4

只是一个观察（我不能添加评论）。

您将收到以下消息：

弃用警告：不推荐使用数字样式的类型代码，将来会导致错误。

不要将 np.fromstring 与二进制文件一起使用。而不是 signal = np.fromstring(signal, 'Int16')，最好使用 signal = np.frombuffer(signal, dtype='int16')。

Answer 5

这是绘制波形文件的波形和频谱的代码

import wave
import numpy as np
import matplotlib.pyplot as plt

signal_wave = wave.open('voice.wav', 'r')
sample_rate = 16000
sig = np.frombuffer(signal_wave.readframes(sample_rate), dtype=np.int16)

对于整个波形文件段

sig = sig[:]

对于波形文件的部分片段

sig = sig[25000:32000]

分离立体声通道

left, right = data[0::2], data[1::2]

绘制波形 (plot_a) 和频谱 (plot_b)

plt.figure(1)

plot_a = plt.subplot(211)
plot_a.plot(sig)
plot_a.set_xlabel('sample rate * time')
plot_a.set_ylabel('energy')

plot_b = plt.subplot(212)
plot_b.specgram(sig, NFFT=1024, Fs=sample_rate, noverlap=900)
plot_b.set_xlabel('Time')
plot_b.set_ylabel('Frequency')

plt.show()

Answer 6

这是处理单声道/立体声和 8 位/16 位 PCM 的版本。

import matplotlib.pyplot as plt
import numpy as np
import wave

file = 'test.wav'

wav_file = wave.open(file,'r')

#Extract Raw Audio from Wav File
signal = wav_file.readframes(-1)
if wav_file.getsampwidth() == 1:
    signal = np.array(np.frombuffer(signal, dtype='UInt8')-128, dtype='Int8')
elif wav_file.getsampwidth() == 2:
    signal = np.frombuffer(signal, dtype='Int16')
else:
    raise RuntimeError("Unsupported sample width")

# http://schlameel.com/2017/06/09/interleaving-and-de-interleaving-data-with-python/
deinterleaved = [signal[idx::wav_file.getnchannels()] for idx in range(wav_file.getnchannels())]

#Get time from indices
fs = wav_file.getframerate()
Time=np.linspace(0, len(signal)/wav_file.getnchannels()/fs, num=len(signal)/wav_file.getnchannels())

#Plot
plt.figure(1)
plt.title('Signal Wave...')
for channel in deinterleaved:
    plt.plot(Time,channel)
plt.show()