"""This file contains utility functions relating to tests and simulations of the decoders."""


import numpy as np
import typing
from tqdm import tqdm

from utility import noise


def count_bit_errors(d: np.array, d_hat: np.array) -> int:
    """Count the number of wrong bits in a decoded codeword.

    :param d: Originally sent data
    :param d_hat: Received data
    :return: Number of bit errors
    """
    return np.sum(d != d_hat)


def test_decoder(encoder: typing.Any,
                 decoder: typing.Any,
                 d: np.array,
                 SNRs: typing.Sequence[float] = np.linspace(1, 4, 7),
                 target_bit_errors: int = 100,
                 N_max: int = 10000) \
        -> typing.Tuple[np.array, np.array]:
    """Calculate the Bit Error Rate (BER) for a given decoder for a number of SNRs.

    This function prints its progress to stdout.

    :param encoder: Instance of the encoder used to generate the codeword to transmit
    :param decoder: Instance of the decoder to be tested
    :param d: Dataword (element of [0, 1]^n)
    :param SNRs: List of SNRs for which the BER should be calculated
    :param target_bit_errors: Number of bit errors after which to stop the simulation
    :param N_max: Maximum number of iterations to perform for each SNR
    :return: Tuple of numpy arrays of the form (SNRs, BERs)
    """

    x = encoder.encode(d)

    BERs = []
    for SNR in tqdm(SNRs, desc="Calculating Bit-Error-Rates",
                    position=0,
                    leave=False,
                    bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt}"):

        total_bit_errors = 0
        total_bits = 0

        for n in tqdm(range(N_max), desc=f"Simulating for SNR = {SNR} dB",
                      position=1,
                      leave=False,
                      bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt}"):

            # TODO: Is this a valid simulation? Can we just add AWGN to the codeword,
            #  ignoring and modulation and (e.g. matched) filtering?
            y = noise.add_awgn(x, SNR, signal_amp=np.sqrt(2))

            y_hat = decoder.decode(y)

            total_bit_errors += count_bit_errors(d, y_hat)
            total_bits += d.size

            if total_bit_errors >= target_bit_errors:
                break

        BERs.append(total_bit_errors / total_bits)

    return np.array(SNRs), np.array(BERs)