Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Scripts for dealing with preparation of offline gracedb upload files #4534

Merged
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
85 changes: 85 additions & 0 deletions bin/all_sky_search/pycbc_make_bayestar_skymap
Original file line number Diff line number Diff line change
@@ -0,0 +1,85 @@
#!/usr/bin/env python

"""
Simple wrapper around bayestar-localize-coincs to get sky localization for a
specific compact binary merger event.
Uses an XML containing SNR timeseries and PSD and calls BAYESTAR to produce a
sky localization.
The wrapper needs to exist as the XML format doesnt allow us to indicate
the low frequency cutoff or waveform used. We also want to be able to control
the output filename which is not possible in bayestar-localize-coincs
Unrecognised options will be passed straight to the bayestar subprocess
"""

import argparse
import subprocess
import shutil
import logging
import os
import glob
import sys
import random
import tempfile
import pycbc.version
from pycbc import init_logging

parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('--version', action="version",
version=pycbc.version.git_verbose_msg)
parser.add_argument('--verbose', action='count',
help="Make the logging increasingly more verbose")
parser.add_argument('--bayestar-executable',
help="The bayestar-localize-coinc executable to be run. "
"If not given, will use whatever is available in "
"the current environment.")
parser.add_argument('--event-xml', required=True,
help="XML file containing event information, SNR "
"timeseries and PSD to pass to bayestar")
parser.add_argument('--waveform', default='TaylorF2',
help="Waveform used in the matched-filtering "
"to generate the SNR timeseries.")
parser.add_argument('--low-frequency-cutoff', type=float, default=20,
help="Low-frequency cutoff used in the matched-filtering "
"to generate the SNR timeseries")
parser.add_argument('--output-file', required=True,
help="Filename to output the fits file to.")
args, unknown = parser.parse_known_args()

# Default logging is set higher than normal for this job
logging_level = args.verbose + 1 if args.verbose else None
init_logging(logging_level)
logging.info("Starting")

bayestar_exe = args.bayestar_executable or 'bayestar-localize-coincs'

tmpdir = tempfile.mkdtemp()

# Set up the command to pass to bayestar.
# The XML file path being passed twice is a legacy requirement, not a mistake.
cmd = [bayestar_exe,
args.event_xml,
args.event_xml,
'--waveform', args.waveform,
'--f-low', str(args.low_frequency_cutoff),
'-o', tmpdir]

# Pass any unknown options straight to the subprocess
cmd += unknown

logging.info("Running %s", ' '.join(cmd))
subprocess.check_output(cmd)

# Find the fits file in the temporary directory:
# It would be nice to do this better! - maybe use the input xml
# file to find the number which is going to be used?
fits_filenames = glob.glob(os.path.join(tmpdir, '*.fits*'))
if len(fits_filenames) != 1:
raise ValueError(f'argh, got {len(fits_filenames)} FITS files after running BAYESTAR, I want one!')

logging.info("Moving output to %s", args.output_file)
shutil.move(fits_filenames[0], args.output_file)

logging.info("Done")
238 changes: 238 additions & 0 deletions bin/all_sky_search/pycbc_prepare_xml_for_gracedb
Original file line number Diff line number Diff line change
@@ -0,0 +1,238 @@
#!/usr/bin/env python

# Copyright (C) 2015-2023 Ian Harry, Gareth Cabourn Davies
#
# This program is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 3 of the License, or (at your
# option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
# Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.

"""
Take a coinc xml file containing multiple events and prepare one of them
for upload to gracedb.
"""

import argparse
import logging
import numpy as np
import h5py
import matplotlib
matplotlib.use('agg')

import pycbc
import lal
import lal.series
from ligo.lw import lsctables
from ligo.lw import utils as ligolw_utils
from ligo.segments import segment, segmentlist
from pycbc.io.ligolw import (
LIGOLWContentHandler,
snr_series_to_xml,
)
from pycbc.psd import interpolate
from pycbc.types import FrequencySeries, TimeSeries, load_timeseries
from pycbc.types import MultiDetOptionAction
from pycbc.results import generate_asd_plot, generate_snr_plot

parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--verbose", action='count',
help="Increase logging level, default=info")
parser.add_argument("--psd-files", nargs='+', required=True,
help='HDF file(s) containing the PSDs to upload')
parser.add_argument("--snr-timeseries", nargs='+', required=True,
help='HDF file(s) containing the SNR timeseries to upload')
parser.add_argument('--input-file', required=True, type=str,
help='Input LIGOLW XML file of coincidences.')
parser.add_argument('--event-id', type=int, required=True,
help='ID for the event being prepared.')
parser.add_argument('--output-file',
help="Output filename for the locally stored XML. ")
parser.add_argument('--snr-timeseries-plot',
help="Output filename for the plot of SNR timeseries. "
"Must be a plot filetype as used by matplotlib.")
parser.add_argument('--psd-plot',
help="Output filename for the plot of the PSD. "
"Must be a plot filetype as used by matplotlib.")
parser.add_argument('--channel-name', action=MultiDetOptionAction,
required=True,
help="Channel name for adding to the uploaded single "
"inspiral table.")
parser.add_argument('--delta-f', type=float, default=0.25,
help="Frequency spacing of the PSD to be uploaded, Hz. "
"Default 0.25")

args = parser.parse_args()

if args.verbose:
args.verbose += 1
else:
args.verbose = 1
pycbc.init_logging(args.verbose)

xmldoc = ligolw_utils.load_filename(args.input_file,
contenthandler=LIGOLWContentHandler)

class psd_segment(segment):
def __new__(cls, psd, *args):
return segment.__new__(cls, *args)
def __init__(self, psd, *args):
self.psd = psd

def read_psds(psd_files):
logging.info("Reading PSDs")
psds = {}

for psd_file in psd_files:
(ifo, group), = h5py.File(psd_file, "r").items()
psd = [group["psds"][str(i)] for i in range(len(group["psds"].keys()))]
psds[ifo] = segmentlist(psd_segment(*segargs) for segargs in zip(
psd, group["start_time"], group["end_time"]))
return psds

psds = read_psds(args.psd_files)

def read_snr_timeseries(snr_timeseries_files):
"""
Get information from the single_template snr timeseries files
"""
logging.info("Reading SNR timeseries")
snr_timeseries = {}
for snr_filename in snr_timeseries_files:
with h5py.File(snr_filename, 'r') as snr_f:
ifo = snr_f.attrs['ifo']
time = snr_f.attrs['event_time']
snr_timeseries[(ifo, time)] = load_timeseries(snr_filename, 'snr')
return snr_timeseries

snr_timeseries = read_snr_timeseries(args.snr_timeseries)

coinc_table = lsctables.CoincTable.get_table(xmldoc)
coinc_inspiral_table = lsctables.CoincInspiralTable.get_table(xmldoc)
coinc_event_map_table = lsctables.CoincMapTable.get_table(xmldoc)
sngl_inspiral_table = lsctables.SnglInspiralTable.get_table(xmldoc)

xmldoc.childNodes[-1].removeChild(sngl_inspiral_table)
xmldoc.childNodes[-1].removeChild(coinc_event_map_table)
xmldoc.childNodes[-1].removeChild(coinc_inspiral_table)
xmldoc.childNodes[-1].removeChild(coinc_table)

# Find the coinc_table entry corresponding to the desired event ID
for event in coinc_table:
coinc_event_id = event.coinc_event_id
if args.event_id == coinc_event_id:
# This is the event we want
break
else:
raise ValueError(f"event {args.event_id} not found in coinc table")

coinc_event_table_curr = lsctables.New(lsctables.CoincTable)
coinc_event_table_curr.append(event)
coinc_inspiral_table_curr = lsctables.New(lsctables.CoincInspiralTable)
coinc_event_map_table_curr = lsctables.New(lsctables.CoincMapTable)
sngl_inspiral_table_curr = lsctables.New(lsctables.SnglInspiralTable)

for coinc_insp in coinc_inspiral_table:
if coinc_insp.coinc_event_id == event.coinc_event_id:
coinc_inspiral_table_curr.append(coinc_insp)

time = coinc_inspiral_table_curr[0].end_time \
+ coinc_inspiral_table_curr[0].end_time_ns * 1e-9

sngl_ids = []
for coinc_map in coinc_event_map_table:
if coinc_map.coinc_event_id == event.coinc_event_id:
coinc_event_map_table_curr.append(coinc_map)
sngl_ids.append(coinc_map.event_id)

# Get the SNR timeseries and PSDs at the time of this event
# these may not have contributed a trigger

# Check that the SNR timeseries correspond to the event
# - allow 0.5s either side of the time
snr_ts = {}
for ifo, t in snr_timeseries.keys():
if not abs(t - time) < 0.5:
raise ValueError("SNR timeseries for IFO %s does not look like it "
"corresponds to this event, event time %.3f, SNR timeseries is "
"around time %.3f" % (ifo, time, t))
# Convert the SNR dict to be keyed on IFO-only:
snr_ts[ifo] = snr_timeseries[(ifo, t)]

# IFOs from SNR timeseries:
psds_event = {}
psddict = {}
for ifo in snr_ts.keys():
psd = psds[ifo]

psd = psd[psd.find(time)].psd
# resample the psd to new spacing
psd_fs = FrequencySeries(psd, delta_f=psd.attrs["delta_f"],
dtype=np.float64)
psd_fs = interpolate(psd_fs, args.delta_f)

psds_event[ifo] = psd
psddict[ifo] = psd_fs

lal_psddict = {}
sample_freqs = {}

for sngl in sngl_inspiral_table:
if sngl.event_id not in sngl_ids:
continue
sngl_inspiral_table_curr.append(sngl)
sngl.channel = args.channel_name[sngl.ifo]

# Two versions of the PSD dictionary have useful info here
psd = psds_event[sngl.ifo]
psd_fs = psddict[sngl.ifo]

flow = psd.file.attrs['low_frequency_cutoff']
kmin = int(flow / args.delta_f)

fseries = lal.CreateREAL8FrequencySeries(
"psd",
lal.LIGOTimeGPS(int(psd.attrs["epoch"])),
kmin * args.delta_f,
args.delta_f,
lal.StrainUnit**2 / lal.HertzUnit,
len(psd_fs) - kmin)
fseries.data.data = psd_fs[kmin:] / np.square(pycbc.DYN_RANGE_FAC)
lal_psddict[sngl.ifo] = fseries

snr_series_to_xml(snr_ts[sngl.ifo], xmldoc, sngl.event_id)

xmldoc.childNodes[-1].appendChild(coinc_event_table_curr)
xmldoc.childNodes[-1].appendChild(coinc_inspiral_table_curr)
xmldoc.childNodes[-1].appendChild(coinc_event_map_table_curr)
xmldoc.childNodes[-1].appendChild(sngl_inspiral_table_curr)
lal.series.make_psd_xmldoc(lal_psddict, xmldoc.childNodes[-1])

ligolw_utils.write_filename(xmldoc, args.output_file)
logging.info("Saved XML file %s", args.output_file)

if args.psd_plot:
logging.info("Saving ASD plot %s", args.psd_plot)
generate_asd_plot(psddict, args.psd_plot)

if args.snr_timeseries_plot:
triggers = {sngl.ifo: (sngl.end_time + sngl.end_time_ns * 1e-9, sngl.snr)
for sngl in sngl_inspiral_table_curr}
base_time = int(np.floor(time))
logging.info("Saving SNR plot %s", args.snr_timeseries_plot)
generate_snr_plot(
snr_ts,
args.snr_timeseries_plot,
triggers,
base_time
)

logging.info('Done!')
Loading
Loading