def primary_vetoed(starttime=None, hveto_path=None, snr=6.0, significance=5.0):
"""Catalogue all vetoed primary triggers from a given analysis
This utility queries the output of an hveto analysis for the triggers
vetoed from its primary channel over all rounds (up to thresholds on
signal-to-noise ratio and round significance).
Parameters
----------
starttime : `str` or `float`
start GPS time for this analysis
hveto_path : 'str'
path of the hveto files directory,
not required if ``starttime`` is given
snr : `float`, optional
signal-to-noise ratio threshold on triggers, default: 6.0
significance : `float`, optional
hveto significance threshold on auxiliary channels, default: 5.0
Returns
-------
catalogue : `~gwpy.table.EventTable`
a tabular catalogue of primary triggers vetoed in the hveto run
"""
path = const.get_hvetopath(starttime) if starttime else hveto_path
t_vetoed = EventTable(names=[
'time', 'snr', 'peak_frequency', 'channel', 'winner', 'significance'
])
try:
files = glob.glob(os.path.join(path, 'triggers', '*VETOED*.txt'))
t_summary = EventTable.read(os.path.join(path, 'summary-stats.txt'),
format='ascii')
n = len(t_summary)
files = files[:n]
t_vetoed = EventTable.read(files, format='ascii')
lenoffiles = t_summary['nveto']
winsig = [
round(t_summary['significance'][i], 4) for i in range(n)
for j in range(lenoffiles[i])
]
winchans = [
t_summary['winner'][i] for i in range(n)
for j in range(lenoffiles[i])
]
rounds = [i + 1 for i in range(n) for j in range(lenoffiles[i])]
colsig = Column(data=winsig, name='significance')
colwin = Column(data=winchans, name='winner')
colround = Column(data=rounds, name='round')
t_vetoed.add_column(colwin)
t_vetoed.add_column(colsig)
t_vetoed.add_column(colround)
t_vetoed = t_vetoed.filter('snr>{0}'.format(snr),
'significance>{0}'.format(significance))
except (FileNotFoundError, ValueError):
warnings.warn("Could not find Hveto analysis for this day")
return t_vetoed
def get_triggers(channel,
etg,
segments,
cache=None,
snr=None,
frange=None,
raw=False,
trigfind_kwargs={},
**read_kwargs):
"""Get triggers for the given channel
"""
etg = _sanitize_name(etg)
# format arguments
try:
readfmt = read_kwargs.pop("format", DEFAULT_FORMAT[etg])
except KeyError:
raise ValueError("unsupported ETG {!r}".format(etg))
trigfind_kwargs, read_kwargs = _format_params(channel, etg, readfmt,
trigfind_kwargs, read_kwargs)
# find triggers
if cache is None:
cache = find_trigger_files(channel, etg, segments, **trigfind_kwargs)
# read files
tables = []
for segment in segments:
segaslist = SegmentList([segment])
segcache = io_cache.sieve(cache, segment=segment)
# try and work out if cache overextends segment (so we need to crop)
cachesegs = io_cache.cache_segments(segcache)
outofbounds = abs(cachesegs - segaslist)
if segcache:
if len(segcache) == 1: # just pass the single filename
segcache = segcache[0]
new = EventTable.read(segcache, **read_kwargs)
new.meta = {k: new.meta[k] for k in TABLE_META if new.meta.get(k)}
if outofbounds:
new = new[in_segmentlist(new[new.dtype.names[0]], segaslist)]
tables.append(new)
if len(tables):
table = vstack_tables(tables)
else:
table = EventTable(
names=read_kwargs.get('columns', ['time', 'frequency', 'snr']))
# parse time, frequency-like and snr-like column names
columns = table.dtype.names
tcolumn = columns[0]
fcolumn = columns[1]
scolumn = columns[2]
# filter
keep = numpy.ones(len(table), dtype=bool)
if snr is not None:
keep &= table[scolumn] >= snr
if frange is not None:
keep &= table[fcolumn] >= frange[0]
keep &= table[fcolumn] < frange[1]
table = table[keep]
# return basic table if 'raw'
if raw:
return table
# rename time column so that all tables match in at least that
if tcolumn != "time":
table.rename_column(tcolumn, 'time')
# add channel column to identify all triggers
table.add_column(
table.Column(data=numpy.repeat(channel, len(table)), name='channel'))
table.sort('time')
return table
def get_triggers(channel, etg, segments, cache=None, snr=None, frange=None,
raw=False, trigfind_kwargs={}, **read_kwargs):
"""Get triggers for the given channel
"""
etg = _sanitize_name(etg)
# format arguments
try:
readfmt = read_kwargs.pop("format", DEFAULT_FORMAT[etg])
except KeyError:
raise ValueError("unsupported ETG {!r}".format(etg))
trigfind_kwargs, read_kwargs = _format_params(
channel,
etg,
readfmt,
trigfind_kwargs,
read_kwargs
)
# find triggers
if cache is None:
cache = find_trigger_files(channel, etg, segments, **trigfind_kwargs)
# read files
tables = []
for segment in segments:
segaslist = SegmentList([segment])
segcache = io_cache.sieve(cache, segment=segment)
# try and work out if cache overextends segment (so we need to crop)
cachesegs = io_cache.cache_segments(segcache)
outofbounds = abs(cachesegs - segaslist)
if segcache:
if len(segcache) == 1: # just pass the single filename
segcache = segcache[0]
new = EventTable.read(segcache, **read_kwargs)
new.meta = {k: new.meta[k] for k in TABLE_META if new.meta.get(k)}
if outofbounds:
new = new[new[new.dtype.names[0]].in_segmentlist(segaslist)]
tables.append(new)
if len(tables):
table = vstack_tables(tables)
else:
table = EventTable(names=read_kwargs.get(
'columns', ['time', 'frequency', 'snr']))
# parse time, frequency-like and snr-like column names
columns = table.dtype.names
tcolumn = columns[0]
fcolumn = columns[1]
scolumn = columns[2]
# filter
keep = numpy.ones(len(table), dtype=bool)
if snr is not None:
keep &= table[scolumn] >= snr
if frange is not None:
keep &= table[fcolumn] >= frange[0]
keep &= table[fcolumn] < frange[1]
table = table[keep]
# return basic table if 'raw'
if raw:
return table
# rename time column so that all tables match in at least that
if tcolumn != "time":
table.rename_column(tcolumn, 'time')
# add channel column to identify all triggers
table.add_column(table.Column(data=numpy.repeat(channel, len(table)),
name='channel'))
table.sort('time')
return table
