[SciPy-User] parsing a wave file
Fri Feb 24 05:26:02 CST 2012
On Thu, Feb 23, 2012 at 9:08 AM, Friedrich Romstedt
> Am 23.02.2012 um 12:04 schrieb David Hutto <email@example.com>:
>> f = Sndfile(r'c:\Users\david\test01.wav', 'r')
> Sorry for the probably dumb question, but where does "Sndfile" originate from?
An online example.
A quick search in the Python 2.6.5 docs
I'm using 2.7.2
and in the online scipy docs yields nothing.
It was a .dll to access functions from I believe.
>> fs = f.samplerate
>> nc = f.channels
>> enc = f.encoding
>> data = f.read_frames(1000)
>> frame_amount = 1000
>> data_float = f.read_frames(frame_amount, dtype=np.float32)
>> for i in range(0,frame_amount,1):
>> print data_float[i]
>> returns data_float[i] in the form:
> It looks to me as if the "Sndfile" instance already decomposes into channels. In the wave file, the channels are intermingled, one frame per channel for each time instance (I'm not fully sure if "frame" denotes the full chunk for one time instance or only one datum for one channel, part of the chunk).
>> Any suggestions as to what I'm parsing in the wrong way, or better
>> solutions than the above?
> I could imagine that the Sndfile class you're using takes the sampling width (i.e., the number of bytes per sample) from the dtype you're handing over, interpreting the originally possible integer-valued frames as float32's. This could also alter the alignment, so that full garbage would result, possibly explaining the apparently highly variable output (as far as I can judge from the two chunks you provided). But notice, this is only guessing, speculation so to speak.
> I've made positive experience with using the wave module from the standard library. I wrote a module (part of a larger sound analysis suite) to
I'd like to see that, or any quicker ways there might be of having the
values of the device immediately, which I'm getting around to now,
instead of having to wait for the wav file.
read arbitrary wave files as long as they are integer-valued. The
module reads the file into a numpy array with sufficient speed (a few
seconds for a 3' piece), and separates the channels. I guess it could
be easily adapted to your use case (currently the channels are
averaged in the end; you would just have to leave that step out). I
would give it to you as a public domain module.
> For the scipy.io.wavfile module, that should work too, although I don't know if it already separates the channels or not—I never used it so far.
I changed it to
import scipy.io.wavfile as wv
for array_val in wv.read(r'c:\Users\david\test01.wav'):
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