Computes the log likelihood.

    This function computes the log likelihood between two numbers,
    or for element between a pair of lists or numpy arrays.

    Parameters
    ----------
    actual : int, float, list of numbers, numpy array
             The ground truth value
    predicted : same type as actual
                The predicted value

    Returns
    -------
    score : double or list of doubles
            The log likelihood error between actual and predicted

def ll(actual, predicted):
    """
    Computes the log likelihood.

    This function computes the log likelihood between two numbers,
    or for element between a pair of lists or numpy arrays.

    Parameters
    ----------
    actual : int, float, list of numbers, numpy array
             The ground truth value
    predicted : same type as actual
                The predicted value

    Returns
    -------
    score : double or list of doubles
            The log likelihood error between actual and predicted

    """
    actual = np.array(actual)
    predicted = np.array(predicted)
    err = np.seterr(all='ignore')
    score = -(actual*np.log(predicted)+(1-actual)*np.log(1-predicted))
    np.seterr(divide=err['divide'], over=err['over'],
              under=err['under'], invalid=err['invalid'])
    if type(score)==np.ndarray:
        score[np.isnan(score)] = 0
    else:
        if np.isnan(score):
            score = 0
    return score