import numpy
import numpy as np
from scipy.signal import firwin, lfilter, decimate
import soundfile

def load_pdm_file(filename):
    with open(filename, 'rb') as f:
        byte_data = np.frombuffer(f.read(), dtype=np.uint8)
    bit_data = np.unpackbits(byte_data)
    # Convert to +1 (for 1s) and -1 (for 0s)
    #pdm_signal = 2 * bit_data - 1
    pdm_signal = bit_data
    return pdm_signal

def pdm_to_pcm(pdm_signal, decimation_factor=64):
    # Design a low-pass filter
    fir_filter = firwin(numtaps=101, cutoff=0.5/decimation_factor)
    # Filter the PDM signal
    filtered = lfilter(fir_filter, [1.0], pdm_signal)
    # Decimate (downsample)
    pcm_signal = filtered[::decimation_factor]
    return pcm_signal

def parse():
    import argparse

    parser = argparse.ArgumentParser(description='Process an input file and write to an output file.')
    parser.add_argument('-i', '--input', type=str, required=True, help='Path to the input file')
    parser.add_argument('-o', '--output', type=str, required=True, help='Path to the output file')
    parser.add_argument('--samplerate', type=int, default=16000)
    parser.add_argument('--oversample', type=int, default=64)
    
    args = parser.parse_args()
    return args

def main():
    args = parse()

    pdm_path = args.input
    out_path = args.output
    pdm_data = load_pdm_file(pdm_path)

    # Convert to PCM
    oversample = args.oversample
    samplerate = args.samplerate
    pcm_data = pdm_to_pcm(pdm_data, decimation_factor=oversample)

    # Normalize and save to WAV
    pcm_data = np.expand_dims(pcm_data, axis=1)
    #print(pcm_data.shape)

    pcm_data -= numpy.mean(pcm_data) # remove DC offset
    print(numpy.min(pcm_data), numpy.max(pcm_data), numpy.mean(pcm_data), pcm_data.dtype)

    soundfile.write(out_path, pcm_data, samplerate)
    print('Wrote', out_path)

if __name__ == '__main__':
    main()