I am a numpy newbie.
I have two wav files, one that numpy takes a long time to process the FFT. They was created within audacity using white noise and silence for gaps.
The files are very similar in the following way;
1. is white noise with silence gaps on every 15 second interval.
2. is 1. but slightly shorter, i.e. I trimmed some ms off the end but it still has the last gap at 60s.
The code I am using processes the file like this;
framerate, data = scipy.io.wavfile.read(filepath)
right = data[:, 0]
# Align it to be efficient.
if len(right) % 2 != 0:
right = right[range(len(right) - 1)]
noframes = len(right)
fftout = np.fft.fft(right) / noframes # <<< I am timing this cmd
Could someone tell me why this behaviour is happening please?
Sorry I can't attach the files as this email gets bounced but you could easily create the files yourself.
E.g my last gap width is 59.9995 - 1:00.0005, I repeat this every 15 seconds.
My truncated file is 1:00.0015s long, non-truncated is 1:00.0833s long