def test_construction_by_name_value_pairs(self):
self.event = events.Event(time=3.3, typ='c', seq=111)
self.assertEqual(111, self.event.seq)
self.assertEqual(3.3, self.event.time)
self.assertEqual('c', self.event.typ)
self.assertIsNone(self.event.end)
self.assertIsNone(self.event.val)
def test_story004(self):
# Order events in reverse by their name and then strip times to
# convert to sequences. Number events starting at 1.
rev_evs_to_seqs = sequences.make_timeline_to_sequence_flattener(
ordering=lambda evs: sorted(evs, key=lambda e: e.typ, reverse=True
),
start=1)
seqs = (
data.seq_concurrent_events,
data.seq_sorted,
data.seq_rand1_08,
)
index_maps = (
(2, 1, 0, 6, 5, 4, 3, 8, 7, 13, 12, 11, 10, 9),
(1, 2, 0, 3, 4, 6, 5, 9, 8, 7, 10),
(1, 0, 4, 3, 2, 5, 6, 7),
)
expected = []
for seq_idx, seq in enumerate(seqs):
for ev_num, ev_idx in enumerate(index_maps[seq_idx], 1):
ev = seq[ev_idx]
expected.append(
events.Event(ev.seq, ev_num, ev.end, ev.typ, ev.val))
actual = list(
streams.map_sequences_as_events(rev_evs_to_seqs,
itools.chain.from_iterable(seqs)))
self.assertEqual(expected, actual)
def test_hash(self):
event2 = events.Event(*self.event_fields)
self.assertEqual(hash(self.event), hash(event2))
def test_eq(self):
event2 = events.Event(*self.event_fields)
self.assertEqual(self.event, event2)
def setUp(self):
self.event = events.Event(*self.event_fields)
def test_matches_nones(self):
event = events.Event()
self.assertTrue(event.matches())
self.assertTrue(event.matches(None, None, None, None, None))
def test_timeline_to_sequence(self):
expected = list(data.seq_rand2_15)
for idx, ev in enumerate(expected):
expected[idx] = events.Event(ev.seq, idx, ev.end, ev.typ, ev.val)
actual = list(sequences.timeline_to_sequence(data.seq_rand2_15))
self.assertEqual(expected, actual)
(1, 0, 'a'),
(7, 6, 'b'),
(1, 0, 'e'),
(6, 3, 'e'),
(1, 8, 'd'),
(3, 3, 'f'),
(3, 3, 'e'),
(1, 3, 'c'),
(6, 8, 'e'),
(4, 1, 'e'),
(9, 7, 'd'),
) # 94
# Event tuples for binary events
binary_events = tuple(
map(lambda tup: events.Event(seq=tup[0], time=tup[1], typ=tup[2]),
binary_event_tuples))
# Specific event sequences to be used in preference to indexing events
seq_len1 = binary_events[0:1]
seq_abcdef = binary_events[9:15]
seq_concurrent_events = binary_events[15:29]
seq_unsorted = binary_events[29:40]
seq_sorted = binary_events[40:51]
seq_rand1_08 = binary_events[51:59]
seq_rand2_15 = binary_events[59:74]
evs_for_selection = binary_events[74:94]
# Drug and condition events for example medical data
drugs = (
'd_ace_inhibitor',
