def METHOD_NAME(params, sub_data, cols, date_col):
    """Apply the weekday adjustment to a specific time series.
    Extracts the weekday fixed effects from the parameters and uses these to
    adjust the time series.
    Since
    log(numerator_t / denominator_t) = alpha_{wd(t)} + phi_t,
    we have that
    numerator_t / denominator_t = exp(alpha_{wd(t)}) exp(phi_t)
    and can divide by exp(alpha_{wd(t)}) to get a weekday-corrected ratio. In
    this case, we only divide the numerator, leaving the denominator unchanged
    -- this has the same effect.
    """
    tmp = sub_data.copy()
    for i, c in enumerate(cols):
        wd_correction = np.zeros((len(tmp[c])))
        for wd in range(7):
            mask = tmp[date_col].dt.dayofweek == wd
            wd_correction[mask] = tmp.loc[mask, c] / (
                np.exp(params[i, wd]) if wd < 6 else np.exp(-np.sum(params[i, :6]))
            )
        tmp.loc[:, c] = wd_correction
    return tmp