Writing WAV file using Python, Numpy array and WAVE module

Question

I am trying to implement the Karplus-Strong algorithm.

All is looking fine when I play (through Jupyter Notebook using Audio(y, rate=Fs)) the collected numpy array (representing guitar accord).

Unfortunately, writing the numpy array: y, into wav file using WAVE module is incorrect (using the next python code):

noise_output = wave.open('k-s.wav', 'w')
noise_output.setparams((1, 4, Fs, 0, 'NONE', 'not compressed'))

for i in range(0, len(y)):
     value = y[i]
     packed_value = struct.pack('f', value)
     noise_output.writeframes(packed_value)

noise_output.close()

Each element of y is

<type 'numpy.float64'>

How should I amend the writing loop in order write the WAV file correctly?

Some more information about the issue. Before writing to WAV, the first elements of the y array are:

 [ 0.33659756  0.33659756 -0.43915295 -0.87036152  1.40708988  0.32123558
-0.6889402   1.9739982  -1.29587159 -0.12299964  2.18381762  0.82228042
 0.24593503 -1.28067426 -0.67568838 -0.01843234 -1.830472    1.2729578
-0.56575346  0.55410736]

After writing the elements to the WAV file, close the WAV file and read it again, I got this for the first 20 elements of the collected array:

[ 1051481732  1051481732 -1092560728 -1084305405  1068768133  1050966269
 -1087349149  1073523705 -1079648481 -1107564740  1074512811  1062371576
  1048303204 -1079775966 -1087571478 -1130954901 -1075163928  1067642952
 -1089415880  1057872379]

Answer 1

Here are code samples to write a (stereo) wave file using the wave standard library. I included two examples: one using numpy, and one that doesn't require any dependencies.

Using a numpy array

Note that if your data is in a numpy array, no need for the struct library.

import wave
import numpy as np

samplerate = 44100

# A note on the left channel for 1 second.
t = np.linspace(0, 1, samplerate)
left_channel = 0.5 * np.sin(2 * np.pi * 440.0 * t)

# Noise on the right channel.
right_channel = np.random.random(size=samplerate)

# Put the channels together with shape (2, 44100).
audio = np.array([left_channel, right_channel]).T

# Convert to (little-endian) 16 bit integers.
audio = (audio * (2 ** 15 - 1)).astype("<h")

with wave.open("sound1.wav", "w") as f:
    # 2 Channels.
    f.setnchannels(2)
    # 2 bytes per sample.
    f.setsampwidth(2)
    f.setframerate(samplerate)
    f.writeframes(audio.tobytes())

Using a list

This is (almost) the same code but without using numpy. No external dependencies are required.

import math
import random
import struct
import wave

samplerate = 44100

left_channel = [
    0.5 * math.sin(2 * math.pi * 440.0 * i / samplerate) for i in range(samplerate)
]
right_channel = [random.random() for _ in range(samplerate)]

with wave.open("sound2.wav", "w") as f:
    f.setnchannels(2)
    f.setsampwidth(2)
    f.setframerate(samplerate)
    for samples in zip(left_channel, right_channel):
        for sample in samples:
            sample = int(sample * (2 ** 15 - 1))
            f.writeframes(struct.pack("<h", sample))