def exclude_tails(records,
to_pe,
min_area=int(2e5),
peak_duration=int(1e4),
tail_duration=int(1e7),
gap_threshold=300):
"""Return records that do not lie fully in tail after a big peak"""
# Find peaks using the records as "hits". This is rough, but good enough.
cut = find_peaks(records,
to_pe,
gap_threshold=gap_threshold,
min_area=min_area,
result_dtype=peak_dtype(records['channel'].max() + 1),
max_duration=peak_duration)
# Transform these 'peaks' to ranges to cut.
# We want to cut tails after peaks, not the peaks themselves.
cut['time'] += peak_duration # Don't cut the actual peak
cut['length'] = tail_duration / cut['dt']
return records[fully_contained_in(records, cut) == -1]
import numpy as np
import numba
from strax import utils
from strax.dtypes import peak_dtype, DIGITAL_SUM_WAVEFORM_CHANNEL
__all__ = 'find_peaks sum_waveform'.split()
@utils.growing_result(dtype=peak_dtype(), chunk_size=int(1e4))
@numba.jit(nopython=True, nogil=True, cache=True)
def find_peaks(hits,
to_pe,
gap_threshold=300,
left_extension=20,
right_extension=150,
min_hits=3,
min_area=0,
max_duration=int(1e9),
_result_buffer=None,
result_dtype=None):
"""Return peaks made from grouping hits together
Assumes all hits have the same dt
:param hits: Hit (or any interval) to group
:param left_extension: Extend peaks by this many ns left
:param right_extension: Extend peaks by this many ns right
:param gap_threshold: No hits for this much ns means new peak
:param min_hits: Peaks with less than min_hits are not returned
:param min_area: Peaks with less than min_area are not returned
:param max_duration: Peaks are forcefully ended after this many ns
"""