"""Utility functions relating to noise and SNR calculations."""


import numpy as np


def get_noise_variance_from_SNR(SNR: float, n: int, k: int) -> float:
    """Calculate the variance of the noise from an SNR and the signal amplitude.

    :param SNR: Signal-to-Noise-Ratio in dB (E_b/N_0)
    :param n: Length of a codeword of the used code
    :param k: Length of a dataword of the used code
    :return: Variance of the noise
    """
    SNR_linear = 10 ** (SNR / 10)
    variance = 1 / (2 * (k/n) * SNR_linear)

    return variance


def add_awgn(c: np.array, SNR: float, n: int, k: int) -> np.array:
    """Add Additive White Gaussian Noise to a data vector. As this function adds random noise to
    the input, the output changes, even if it is called multiple times with the same input.

    :param c: Binary vector representing the data to be transmitted
    :param SNR: Signal-to-Noise-Ratio in dB
    :param n: Length of a codeword of the used code
    :param k: Length of a dataword of the used code
    :return: Data vector with added noise
    """
    noise_var = get_noise_variance_from_SNR(SNR, n, k)
    y = c + np.sqrt(noise_var) * np.random.normal(size=c.size)
    return y