def compute(self, records_nv, start, end):
hits = strax.find_hits(records_nv, min_amplitude=self.config['hit_min_amplitude_nv'])
hits = remove_switched_off_channels(hits, self.to_pe)
temp_hitlets = strax.create_hitlets_from_hits(hits,
self.config['save_outside_hits_nv'],
self.channel_range,
chunk_start=start,
chunk_end=end)
del hits
# Get hitlet data and split hitlets:
temp_hitlets = strax.get_hitlets_data(temp_hitlets, records_nv, to_pe=self.to_pe)
temp_hitlets = strax.split_peaks(temp_hitlets,
records_nv,
self.to_pe,
data_type='hitlets',
algorithm='local_minimum',
min_height=self.config['min_split_nv'],
min_ratio=self.config['min_split_ratio_nv']
)
# Compute other hitlet properties:
# We have to loop here 3 times over all hitlets...
strax.hitlet_properties(temp_hitlets)
entropy = strax.conditional_entropy(temp_hitlets, template='flat', square_data=False)
temp_hitlets['entropy'][:] = entropy
# Remove data field:
hitlets = np.zeros(len(temp_hitlets), dtype=strax.hitlet_dtype())
strax.copy_to_buffer(temp_hitlets, hitlets, '_copy_hitlets')
return hitlets
def make_records_and_hitlets(self, dummy_records):
records = self._make_fake_records(dummy_records)
hits = strax.find_hits(records, min_amplitude=2)
hitlets = strax.create_hitlets_from_hits(hits, (1, 1), (0, 1), 0,
float('inf'))
return records, hitlets
def test_create_hits_from_hitlets_empty_hits():
hits = np.zeros(0, dtype=strax.hit_dtype)
hitlets = strax.create_hitlets_from_hits(hits, (1, 1), (0, 1))
assert len(hitlets) == 0, 'Hitlets should be empty'