wavio

wavio is a Python module that defines two functions:

• wavio.read reads a WAV file and returns an object that holds the sampling rate, sample width (in bytes), and a numpy array containing the data.
• wavio.write writes a numpy array to a WAV file, optionally using a specified sample width.

The functions can read and write 8-, 16-, 24- and 32-bit integer WAV files.

The module uses the wave module in Python's standard library, so it has the same limitations as that module. In particular, the wave module does not support compressed WAV files, and it does not handle floating point WAV files. When floating point data is passed to wavio.write it is converted to integers before being written to the WAV file.

wavio requires Python 3.7 or later.

wavio depends on numpy (). NumPy version 1.19.0 or later is required. The unit tests in wavio require pytest.

The API of the functions in wavio should not be considered stable. There may be backwards-incompatible API changes between releases.

Important notice

In version 0.0.5, the data handling in wavio.write has been changed in a backwards-incompatible way. The API for scaling the input in 0.0.4 was a flexible interface that only its creator could love. The new API is simpler, and it is hoped that it does the right thing by default in most cases. In particular:

• When the input data is an integer type, the values are not scaled or shifted. The only change that might happen is the data will be clipped if the values do not fit in the output integer type.
• If the input data is a floating point type, sampwidth must be given. The default behavior is to scale input values in the range [-1.0, 1.0] to the output range [min_int+1, max_int], where min_int and max_int are the minimum and maximum values of the output data type determined by sampwidth. See the description of scale in the docstring of wavio.write for more options. Regardless of the value of scale, the float input 0.0 is always mapped to the midpoint of the output type; wavio.write will not translate the values up or down.
• A warning is now generated if any data values are clipped. A parameter allows the generation of the warning to be disabled or converted to an exception.

Examples

The following examples are also found in the docstring of wavio.write.

Create a 3 second 440 Hz sine wave, and save it in a 24-bit WAV file.

> >>> import numpy as np >>> import wavio > > >>> rate = 22050 # samples per second >>> T = 3 # > sample duration (seconds) >>> n = int(rate*T) # number of > samples >>> t = np.arange(n)/rate # grid of time values > > >>> f = 440.0 # sound frequency (Hz) >>> x = > np.sin(2*np.pi * f * t)

x is a single sine wave with amplitude 1, so we can use the default scale.

> >>> wavio.write("sine24.wav", x, rate, sampwidth=3)

Create a file that contains the 16 bit integer values -10000 and 10000 repeated 100 times. Use a sample rate of 8000.

> >>> x = np.empty(200, dtype=np.int16) >>> x[::2] = > -10000 >>> x[1::2] = 10000 >>> > wavio.write("foo.wav", x, 8000)

Check that the file contains what we expect. The values are checked for exact equality. The input was an integer array, so the values are not scaled.

> >>> w = wavio.read("foo.wav") >>> np.all(w.data[:, > 0] == x) True

Write floating point data to a 16 bit WAV file. The floating point values are assumed to be within the range [-2, 2], and we want the values 2 and -2 to correspond to the full output range, even if the actual values in the data do not fill this range. We do that by specifying scale=2.

T, rate and t are from above. The data is the sum of two sinusoids, with frequencies 440 and 880 Hz, modulated by a parabolic curve that is zero at the start and end of the data.

> >>> envelope = (4/T*2)(t * (T - t)) >>> omega1 = > 2*np.pi*440 >>> omega2 = 2*np.pi*880 >>> y = > envelope*(np.sin(omega1*t) + 0.3*np.sin(omega2*t + 0.2)) > >>> y.min(), y.max() (-1.1745469775555515, 1.093833464065767)

Write the WAV file, with scale=2.

> >>> wavio.write('harmonic.wav', y, rate, sampwidth=2, > scale=2)

Check the minimum and maximum integers that were actually written to the file:

> >>> w = wavio.read("harmonic.wav") >>> w.data.min(), > w.data.max() (-19243, 17921)

If we want the WAV file to use as much of the range of the output integer type as possible (while still mapping 0.0 in the input to 0 in the output), we set scale="auto".

> >>> wavio.write('harmonic_full.wav', y, rate, sampwidth=2, > scale="auto") > > >>> w = wavio.read('harmonic_full.wav') >>> > w.data.min(), w.data.max() (-32768, 30517)

Author: Warren Weckesser

Repository:

License: BSD 2-clause ()