def compute_segment_lists(seglists, offset_vectors, min_segment_length, pad):
# don't modify original
seglists = seglists.copy()
# ignore offset vectors referencing instruments we don't have
offset_vectors = [offset_vector for offset_vector in offset_vectors if set(offset_vector.keys()).issubset(set(seglists.keys()))]
# cull too-short single-instrument segments from the input
# segmentlist dictionary; this can significantly increase
# the speed of the get_coincident_segmentlistdict()
# function when the input segmentlists have had many data
# quality holes poked out of them
remove_too_short_segments(seglists, min_segment_length, pad)
# extract the segments that are coincident under the time
# slides
new = ligolw_cafe.get_coincident_segmentlistdict(seglists, offset_vectors)
# round to integer boundaries because lalapps_StringSearch can't accept
# non-integer start/stop times
# FIXME: fix that in lalapps_StringSearch
for seglist in new.values():
for i in range(len(seglist)):
seglist[i] = segments.segment(int(math.floor(seglist[i][0])), int(math.ceil(seglist[i][1])))
# intersect with original segments to ensure we haven't expanded beyond
# original bounds
new &= seglists
# again remove too-short segments
remove_too_short_segments(new, min_segment_length, pad)
# done
return new
def compute_segment_lists(seglists, offset_vectors, min_segment_length, pad):
# don't modify original
seglists = seglists.copy()
# ignore offset vectors referencing instruments we don't have
offset_vectors = [
offset_vector for offset_vector in offset_vectors
if set(offset_vector.keys()).issubset(set(seglists.keys()))
]
# cull too-short single-instrument segments from the input
# segmentlist dictionary; this can significantly increase
# the speed of the get_coincident_segmentlistdict()
# function when the input segmentlists have had many data
# quality holes poked out of them
remove_too_short_segments(seglists, min_segment_length, pad)
# extract the segments that are coincident under the time
# slides
new = ligolw_cafe.get_coincident_segmentlistdict(seglists, offset_vectors)
# round to integer boundaries because lalapps_StringSearch can't accept
# non-integer start/stop times
# FIXME: fix that in lalapps_StringSearch
for seglist in new.values():
for i in range(len(seglist)):
seglist[i] = segments.segment(int(math.floor(seglist[i][0])),
int(math.ceil(seglist[i][1])))
# intersect with original segments to ensure we haven't expanded beyond
# original bounds
new &= seglists
# again remove too-short segments
remove_too_short_segments(new, min_segment_length, pad)
# done
return new
def compute_segment_lists(seglistdict, time_slides, minimum_gap, timing_params, full_segments = True, verbose = False): if verbose: print >>sys.stderr, "constructing segment list ..." seglistdict = seglistdict.copy() if not full_segments: # cull too-short single-instrument segments from the input # segmentlist dictionary; this can significantly increase # the speed of the get_coincident_segmentlistdict() # function when the input segmentlists have had many data # quality holes poked out of them power.remove_too_short_segments(seglistdict, timing_params) # extract the segments that are coincident under the time # slides new = ligolw_cafe.get_coincident_segmentlistdict(seglistdict, time_slides) # adjust surviving segment lengths up to the next integer # number of PSDs for seglist in new.values(): # Try Adjusting Upper Bounds: # count the number of PSDs in each segment psds = [power.psds_from_job_length(timing_params, float(abs(seg))) for seg in seglist] # round up to the nearest integer. psds = [int(math.ceil(max(n, 1.0))) for n in psds] # compute the duration of each job durations = [power.job_length_from_psds(timing_params, n) for n in psds] # update segment list for i, seg in enumerate(seglist): seglist[i] = segments.segment(seg[0], seg[0] + durations[i]) # and take intersection with original segments to # not exceed original bounds new &= seglistdict # Try Adjusting Lower Bounds: # count the number of PSDs in each segment psds = [power.psds_from_job_length(timing_params, float(abs(seg))) for seg in seglist] # round up to the nearest integer. psds = [int(math.ceil(max(n, 1.0))) for n in psds] # compute the duration of each job durations = [power.job_length_from_psds(timing_params, n) for n in psds] # update segment list for i, seg in enumerate(seglist): seglist[i] = segments.segment(seg[1] - durations[i], seg[1]) # and take intersection with original segments to # not exceed original bounds new &= seglistdict # try to fill gaps between jobs new.protract(minimum_gap / 2).contract(minimum_gap / 2) # and take intersection with original segments to not # exceed original bounds seglistdict &= new # remove segments that are too short power.remove_too_short_segments(seglistdict, timing_params) # done return seglistdict
def compute_segment_lists(seglistdict, time_slides, minimum_gap, timing_params, full_segments = True, verbose = False): if verbose: print >>sys.stderr, "constructing segment list ..." seglistdict = seglistdict.copy() if not full_segments: # cull too-short single-instrument segments from the input # segmentlist dictionary; this can significantly increase # the speed of the get_coincident_segmentlistdict() # function when the input segmentlists have had many data # quality holes poked out of them power.remove_too_short_segments(seglistdict, timing_params) # extract the segments that are coincident under the time # slides new = ligolw_cafe.get_coincident_segmentlistdict(seglistdict, time_slides) # adjust surviving segment lengths up to the next integer # number of PSDs for seglist in new.values(): # Try Adjusting Upper Bounds: # count the number of PSDs in each segment psds = [power.psds_from_job_length(timing_params, float(abs(seg))) for seg in seglist] # round up to the nearest integer. psds = [int(math.ceil(max(n, 1.0))) for n in psds] # compute the duration of each job durations = [power.job_length_from_psds(timing_params, n) for n in psds] # update segment list for i, seg in enumerate(seglist): seglist[i] = segments.segment(seg[0], seg[0] + durations[i]) # and take intersection with original segments to # not exceed original bounds new &= seglistdict # Try Adjusting Lower Bounds: # count the number of PSDs in each segment psds = [power.psds_from_job_length(timing_params, float(abs(seg))) for seg in seglist] # round up to the nearest integer. psds = [int(math.ceil(max(n, 1.0))) for n in psds] # compute the duration of each job durations = [power.job_length_from_psds(timing_params, n) for n in psds] # update segment list for i, seg in enumerate(seglist): seglist[i] = segments.segment(seg[1] - durations[i], seg[1]) # and take intersection with original segments to # not exceed original bounds new &= seglistdict # try to fill gaps between jobs new.protract(minimum_gap / 2).contract(minimum_gap / 2) # and take intersection with original segments to not # exceed original bounds seglistdict &= new # remove segments that are too short power.remove_too_short_segments(seglistdict, timing_params) # done return seglistdict
