Numpy RFFT/IRFFT volume

Question

I'm doing an rfft and irfft from a wave file:

samplerate, data = wavfile.read(location)
input = data.T[0] # first track of audio
fftData = np.fft.rfft(input[sample:], length)
output = np.fft.irfft(fftData).astype(data.dtype)

So it reads from a file and then does rfft. However it produces a lot of noise when I play the audio with py audio stream. I tried to search an answer to this question and used this solution:

rfft or irfft increasing wav file volume in python

That is why I have the .astype(data.dtype) when doing the irfft. However it doesn't reduce the noise, it reduced it a bit but still it sounds all wrong.

This is the playback, where p is the pyAudio:

stream = p.open(format=pyaudio.paFloat32,
                channels=1,
                rate=fs,
                output=True)

stream.write(output)    
stream.stop_stream()
stream.close()    
p.terminate()

So what am I doing wrong here?

Thanks!

edit: Also I tried to use .astype(dtype=np.float32) when doing the irfft as the pyaudio uses that when streaming audio. However it was still noisy.

Answer 1

The best working solution this far seems to be normalization with median value and using .astype(np.float32) as pyAudio output is float32:

samplerate, data = wavfile.read(location)
input = data.T[0] # first track of audio
fftData = np.fft.rfft(input[sample:], length)
fftData = np.divide(fftData, np.median(fftData))
output = np.fft.irfft(fftData).astype(dtype=np.float32)

If anyone has better solutions I'd like to hear. I tried with mean normalization but it still resulted in clipping audio, normalization with np.max made the whole audio too low. This normalization problem with FFT is always giving me trouble and haven't found any 100% working solutions here in SO.