Python: write a wav file into numpy float array
Solution 1
>>> from scipy.io.wavfile import read
>>> a = read("adios.wav")
>>> numpy.array(a[1],dtype=float)
array([ 128., 128., 128., ..., 128., 128., 128.])
Typically it would be bytes which are then ints... here we just convert it to float type.
You can read about read here: https://docs.scipy.org/doc/scipy/reference/tutorial/io.html#module-scipy.io.wavfile
Solution 2
Seven years after the question was asked...
import wave
import numpy
# Read file to get buffer
ifile = wave.open("input.wav")
samples = ifile.getnframes()
audio = ifile.readframes(samples)
# Convert buffer to float32 using NumPy
audio_as_np_int16 = numpy.frombuffer(audio, dtype=numpy.int16)
audio_as_np_float32 = audio_as_np_int16.astype(numpy.float32)
# Normalise float32 array so that values are between -1.0 and +1.0
max_int16 = 2**15
audio_normalised = audio_as_np_float32 / max_int16
Solution 3
Use librosa
package and simply load wav file to numpy array with:
y, sr = librosa.load(filename)
loads and decodes the audio as a time series y, represented as a one-dimensional NumPy floating point array. The variable sr contains the sampling rate of y, that is, the number of samples per second of audio. By default, all audio is mixed to mono and resampled to 22050 Hz at load time. This behavior can be overridden by supplying additional arguments to librosa.load().
More information at Librosa library documentation
Comments
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IAM almost 2 years
ifile = wave.open("input.wav")
how can I write this file into a numpy float array now?