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.