import numpy as np

TRNG_PAIR_CNT = 64


if __name__ == '__main__':
    # reading info file - length of trace, sampling frequency (not necessary to know in our case), random value generated by the TRNG
    with open("data_info.txt", "r") as fin:
        tracelen = int(fin.readline())
        fs = int(fin.readline())
        trng_val = fin.readline()

    traces = np.fromfile("data.bin", dtype='uint8') # reading traces for individual ROs
    traces = np.reshape(traces, (traces.size//tracelen, tracelen)) # reshape of matrix, each row contains the trace for one RO

    traces_bin = ??? # conversion of waveforms to rectangles - everything below threshold is 0, otherwise 1 (they are boolean values actually)
    rising_edges = np.logical_not(???) & ??? # finding rising edges, each rising edge is represented by True

    cnt = np.count_nonzero(???, axis=1) # count the number of rising edges in rows
    # cnt is now a 1D vector
    cnt = cnt.reshape(TRNG_PAIR_CNT,2).min(axis=1) # Reshape of the count array into matrix, where each row contains 2 values - the number of rising edges for two ROs in a pair. Then we select the smaller value.

    cnt_sel = cnt & ?x???? # select only the two least significant bits

    estimate = ''.join([np.binary_repr(x, width=2) for x in cnt_sel]) # binary representation of the values (the last 2 bits) and joining them into one string
    print('{0:0>32x}'.format(int(estimate, 2)))
    print(trng_val) # from data_info, output of the RNG in FPGA