def testSearchSimilarPatterns_merge(self):
template_start_time = 1
template_duration = 2
template = np.ones((n_leads, template_duration * sampling_freq))
template_span = similarity_pb2.TimeSpan()
template_span.start_time = template_start_time
template_span.duration = template_duration
seen_events = [template_span]
set_slice_value(self.base_data, template, template_start_time,
sampling_freq)
target_1_start_time = 5
set_slice_value(self.base_data, template, target_1_start_time,
sampling_freq)
target_2_start_time = 8.5
set_slice_value(self.base_data, template, target_2_start_time,
sampling_freq)
patterns_found = similarity.SearchSimilarPatterns(
self.base_data,
template_start_time,
template_duration,
seen_events,
sampling_freq,
top_n=2,
merge_close_results=True,
merge_threshold=2)
target_2_end_time = target_2_start_time + template_duration
merged_duration = target_2_end_time - target_1_start_time
merged_targets_span = similarity_pb2.TimeSpan()
merged_targets_span.start_time = target_1_start_time
merged_targets_span.duration = merged_duration
self.assertTrue(overlaps(merged_targets_span, patterns_found[0]))
def testSearchSimilarPatterns_ignoreSeen(self):
template_start_time = 1
template_duration = 1
seen_event = similarity_pb2.TimeSpan()
seen_event.start_time = 10
seen_event.duration = 2.5
patterns_found = similarity.SearchSimilarPatterns(self.base_data,
template_start_time,
template_duration,
[seen_event],
sampling_freq,
top_n=10)
for pattern in patterns_found:
end_time = pattern.start_time + pattern.duration
message = 'Overlaps with event between %s-%s' % (
pattern.start_time, end_time)
self.assertFalse(overlaps(seen_event, pattern), message)
