I have been given a large WAV-file of continuous underwater recording which I would like to convert to a numpy array for analysis. I am struggling to do this.
So far
Here's a loop that handles 2, 3, and 4 byte WAV files with arbitrary numbers of channels:
def dataFromWave(fname):
""" return list with interleaved samples """
f = wave.open(fname, 'rb')
chans = f.getnchannels()
samps = f.getnframes()
sampwidth = f.getsampwidth()
if sampwidth == 3: #have to read this one sample at a time
s = ''
for k in xrange(samps):
fr = f.readframes(1)
for c in xrange(0,3*chans,3):
s += '\0'+fr[c:(c+3)] # put TRAILING 0 to make 32-bit (file is little-endian)
else:
s = f.readframes(samps)
f.close()
unpstr = '<{0}{1}'.format(samps*chans, {1:'b',2:'h',3:'i',4:'i',8:'q'}[sampwidth])
x = list(struct.unpack(unpstr, s))
if sampwidth == 3:
x = [k >> 8 for k in x] #downshift to get +/- 2^24 with sign extension
return x
For those with similar issues I post my solution. Note that this converts a 24-bit wave file into a signed floating point numpy array. Leave the /int2float part out when only converting to integers.
frames = wavfile.readframes(nsamples)
ch1 = np.zeros(nsamples)
ch2 = np.zeros(nsamples)
int2float = (2**23)-1
for x in np.arange(int(nsamples)):
ch1_24bit_sample = frames[x*6:x*6+3]
ch2_24bit_sample = frames[x*6+3:x*6+6]
ch1_32bit_sample = bit24_2_32(ch1_24bit_sample)
ch2_32bit_sample = bit24_2_32(ch2_24bit_sample)
ch1[x]=struct.unpack('i',ch_32bit_sample)[0]
ch2[x]=struct.unpack('i',ch_32bit_sample)[0]
ch1[x]=ch1[x]/int2float
ch2[x]=ch2[x]/int2float
def bit24_2_32(strbytes):
if strbytes[2] < '\x80':
return strbytes+'\x00'
else:
return strbytes+'\xff'
This is an old question but if someone needs additional options and there is no restriction on using external modules, then you can probably use librosa
myNdArray = librosa.core.load(wav_path, sr=sample_rate)[0]