import unittest

from evaluate_streaming import classification, last_available


class CausalStreamingScores(unittest.TestCase):
    def test_startup_future_and_stale_outputs_are_unavailable(self):
        points = [[100, .2], [200, .9], [900, .3]]
        self.assertIsNone(last_available(points, 99, 200))
        self.assertEqual(last_available(points, 150, 200), [100, .2])
        self.assertEqual(last_available(points, 200, 200), [200, .9])
        self.assertEqual(last_available(points, 400, 200), [200, .9])
        self.assertIsNone(last_available(points, 401, 200))
        self.assertEqual(last_available(points, 1000, 200), [900, .3])

    def test_missing_outputs_do_not_count_as_correct_negative_predictions(self):
        rows = [dict(can_reply_now='0', status='unavailable', score=''),
                dict(can_reply_now='0', status='available', score=.7),
                dict(can_reply_now='1', status='available', score=.8),
                dict(can_reply_now='', status='available', score=.1)]
        result = classification(rows)
        self.assertEqual((result['n'], result['requested_labeled'], result['unavailable_labeled']), (2, 3, 1))
        self.assertEqual((result['tn'], result['fp'], result['fn'], result['tp']), (0, 1, 0, 1))
        self.assertEqual(result['accuracy'], .5)

    def test_threshold_is_strict_and_empty_scores_have_no_accuracy(self):
        self.assertEqual(classification([dict(can_reply_now='1',status='available',score=.5)])['fn'], 1)
        result = classification([dict(can_reply_now='0',status='unavailable',score='')])
        self.assertEqual(result['n'], 0)
        self.assertIsNone(result['accuracy'])


if __name__ == '__main__':
    unittest.main()