def evaluate(labels, predictions):
    """
    Given a list of actual labels and a list of predicted labels,
    return a tuple (sensitivity, specificty).

    Assume each label is either a 1 (positive) or 0 (negative).

    `sensitivity` should be a floating-point value from 0 to 1
    representing the "true positive rate": the proportion of
    actual positive labels that were accurately identified.

    `specificity` should be a floating-point value from 0 to 1
    representing the "true negative rate": the proportion of
    actual negative labels that were accurately identified.
    """

    sensitivityPredicted = 0
    sensitivityTotal = 0
    specificityPredicted = 0
    specificityTotal = 0

    for label, predict in zip(labels, predictions):
        if label == 1:
            sensitivityTotal += 1
            if label == predict:
                sensitivityPredicted += 1
        else:
            specificityTotal += 1
            if label == predict:
                specificityPredicted += 1

    return (sensitivityPredicted/sensitivityTotal, specificityPredicted/specificityTotal)