How to plot a wav file

Question

I have just read a wav file with scipy and now I want to make the plot of the file using matplotlib, on the \"y scale\" I want to see the aplitude and over the \"x scale\" I

Answer 1

Just an observation (I cannot add comment).

You will receive the following mesage:

DeprecationWarning: Numeric-style type codes are deprecated and will resultin an error in the future.

Do not use np.fromstring with binaries. Instead of signal = np.fromstring(signal, 'Int16'), it's preferred to use signal = np.frombuffer(signal, dtype='int16').

Answer 2

Alternatively, if you want to use SciPy, you may also do the following:

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

Here is a version that handles mono/stereo and 8-bit/16-bit PCM.

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()

Answer 4

I came up with a solution that's more flexible and more performant:

• Downsampling is used to achieve two samples per second. This is achieved by calculating the average of absolute values for each window. The result looks like the waveforms from streaming sites like SoundCloud.
• Multi-channel is supported (thanks @Alter)
• Numpy is used for each operation, which is much more performant than looping through the array.
• The file is processed in batches to support very large files.

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

file = 'audiofile.wav'

with wave.open(file,'r') as wav_file:
    num_channels = wav_file.getnchannels()
    frame_rate = wav_file.getframerate()
    downsample = math.ceil(frame_rate * num_channels / 2) # Get two samples per second!

    process_chunk_size = 600000 - (600000 % frame_rate)

    signal = None
    waveform = np.array([])

    while signal is None or signal.size > 0:
        signal = np.frombuffer(wav_file.readframes(process_chunk_size), dtype='int16')

        # Take mean of absolute values per 0.5 seconds
        sub_waveform = np.nanmean(
            np.pad(np.absolute(signal), (0, ((downsample - (signal.size % downsample)) % downsample)), mode='constant', constant_values=np.NaN).reshape(-1, downsample),
            axis=1
        )

        waveform = np.concatenate((waveform, sub_waveform))

    #Plot
    plt.figure(1)
    plt.title('Waveform')
    plt.plot(waveform)
    plt.show()

Answer 5

Here's a version that will also handle stereo inputs, based on the answer by @ederwander

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 6

You can call wave lib to read an audio file.

To plot the waveform, use the "plot" function from matplotlib

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()

you will have something like:

To Plot the x-axis in seconds you need get the frame rate and divide by size of your signal, you can use linspace function from numpy to create a Time Vector spaced linearly with the size of the audio file and finally you can use plot again like 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()

New plot x-axis in seconds: