r"""Find the sensitivity that corresponds to the indicated specificity (ROC function)
    sensitivity = Num_True_Positive / (Num_True_Postive + Num_False_Negative)
    specificity = Num_True_Negative / (Num_True_Negative + Num_False_Positive)

def sens_from_spec(spec, labels, scores, *args, **kwargs):
    r"""Find the sensitivity that corresponds to the indicated specificity (ROC function)
    sensitivity = Num_True_Positive / (Num_True_Postive + Num_False_Negative)
    specificity = Num_True_Negative / (Num_True_Negative + Num_False_Positive)
    """
    thresh = thresh_from_spec(spec, labels, scores)
    df = pd.DataFrame(list(zip(labels, scores[scores > thresh].astype(int))))
    c = Confusion(df, *args, **kwargs)
    return c._binary_sensitivity