def sens_from_thresh(thresh, labels, scores, *args, **kwargs):
df = pd.DataFrame(list(zip(labels, np.array(scores > thresh).astype(int))))<EOL>c = Confusion(df, *args, **kwargs)<EOL>return c._binary_sensitivity<EOL>
r"""Compute the specifity that a particular threshold on the scores can acheive
    sensitivity = Num_True_Positive / (Num_True_Postive + Num_False_Negative)
    >>> scores = np.arange(0, 1, 0.1)
    >>> sens_from_thresh(0.5, labels=(scores > .5).astype(int), scores=scores)
    1.0
    >>> sens_from_thresh(0.5, labels=(scores > .4).astype(int), scores=scores)
    0.8