Hi,
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.
my_1_minute_noise_with_gaps.wavmy_1_minute_noise_with_gaps_truncated.wav
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
Using timeit...
my_1_minute_noise_with_gaps_truncated took 30.75620985s to
process.my_1_minute_noise_with_gaps took 22307.13917s to process.
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
Thanks.
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