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Workflow changes needed to manage preparation of offline gracedb uplo…
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,191 @@ | ||
| #!/bin/env python | ||
| # Copyright (C) 2015-2023 Alexander Harvey Nitz, 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. | ||
| """ Prepare files for upload to GraceDB for foreground events | ||
| """ | ||
| import os, sys, argparse, logging, re, h5py, pycbc.workflow as wf | ||
| from pycbc.results import layout | ||
| from pycbc.types import MultiDetOptionAction | ||
| from pycbc.events import select_segments_by_definer, coinc | ||
| from pycbc.io import get_all_subkeys | ||
| import pycbc.workflow.minifollowups as mini | ||
| from pycbc.workflow.core import resolve_url_to_file, resolve_td_option | ||
| from ligo import segments | ||
|
|
||
| import numpy as np | ||
| import pycbc.version | ||
|
|
||
| parser = argparse.ArgumentParser(description=__doc__[1:]) | ||
| parser.add_argument('--verbose', action='count', | ||
| help='Add progressively more verbose output, ' | ||
| 'default=info') | ||
| parser.add_argument('--version', action='version', version=pycbc.version.git_verbose_msg) | ||
| parser.add_argument('--bank-file', | ||
| help="HDF format template bank file") | ||
| parser.add_argument('--statmap-file', | ||
| help="HDF format clustered coincident trigger result file") | ||
| parser.add_argument('--xml-all-file', | ||
| help="XML format result file containing all events") | ||
| parser.add_argument('--single-detector-triggers', nargs='+', action=MultiDetOptionAction, | ||
| help="HDF format merged single detector trigger files") | ||
| parser.add_argument('--inspiral-segments', | ||
| help="xml segment files containing the inspiral analysis times") | ||
| parser.add_argument('--inspiral-data-read-name', | ||
| help="Name of inspiral segmentlist containing data read in " | ||
| "by each analysis job.") | ||
| parser.add_argument('--inspiral-data-analyzed-name', | ||
| help="Name of inspiral segmentlist containing data " | ||
| "analyzed by each analysis job.") | ||
| parser.add_argument('--psd-files', nargs='+', action=MultiDetOptionAction, | ||
| help="HDF format merged single detector PSD files") | ||
| parser.add_argument('--ifar-thresh', type=float, | ||
| help="IFAR threshold for preparing SNR timeseries " | ||
| "files for upload. Default=No upload prep") | ||
|
|
||
| wf.add_workflow_command_line_group(parser) | ||
| wf.add_workflow_settings_cli(parser, include_subdax_opts=True) | ||
| args = parser.parse_args() | ||
|
|
||
| if args.verbose: | ||
| args.verbose += 1 | ||
| else: | ||
| args.verbose = 1 | ||
| pycbc.init_logging(args.verbose) | ||
|
|
||
| workflow = wf.Workflow(args) | ||
|
|
||
| wf.makedir(args.output_dir) | ||
|
|
||
| channel_opts = {} | ||
| for ifo in workflow.ifos: | ||
| channel_opts[ifo] = workflow.cp.get_opt_tags( | ||
| "workflow", | ||
| "%s-channel-name" % ifo.lower(), | ||
| "") | ||
|
|
||
| # create a FileList that will contain all output files | ||
| layouts = [] | ||
|
|
||
| tmpltbank_file = resolve_url_to_file(os.path.abspath(args.bank_file)) | ||
| insp_segs = resolve_url_to_file(os.path.abspath(args.inspiral_segments)) | ||
| xml_all = resolve_url_to_file(os.path.abspath(args.xml_all_file)) | ||
|
|
||
| single_triggers = [] | ||
| psd_files = [] | ||
| fsdt = {} | ||
| insp_data_seglists = {} | ||
| insp_analysed_seglists = {} | ||
| for ifo in args.single_detector_triggers: | ||
| strig_fname = args.single_detector_triggers[ifo] | ||
| strig_file = resolve_url_to_file(os.path.abspath(strig_fname), | ||
| attrs={'ifos': ifo}) | ||
| single_triggers.append(strig_file) | ||
|
|
||
| psd_fname = args.psd_files[ifo] | ||
| psd_file = resolve_url_to_file(os.path.abspath(psd_fname), | ||
| attrs={'ifos': ifo}) | ||
| psd_files.append(psd_file) | ||
|
|
||
| fsdt[ifo] = h5py.File(args.single_detector_triggers[ifo], 'r') | ||
| insp_data_seglists[ifo] = select_segments_by_definer( | ||
| args.inspiral_segments, | ||
| segment_name=args.inspiral_data_read_name, | ||
| ifo=ifo) | ||
| insp_analysed_seglists[ifo] = select_segments_by_definer( | ||
| args.inspiral_segments, | ||
| segment_name=args.inspiral_data_analyzed_name, | ||
| ifo=ifo) | ||
| # NOTE: make_singles_timefreq needs a coalesced set of segments. If this is | ||
| # being used to determine command-line options for other codes, | ||
| # please think if that code requires coalesced, or not, segments. | ||
| insp_data_seglists[ifo].coalesce() | ||
| insp_analysed_seglists[ifo].coalesce() | ||
|
|
||
| f = h5py.File(args.statmap_file, 'r') | ||
| stat = f['foreground/stat'][:] | ||
|
|
||
| bank_data = h5py.File(args.bank_file, 'r') | ||
|
|
||
| ifar_limit = args.ifar_thresh | ||
| # Get indices of all events which pass the IFAR threshold | ||
| event_ifars = f['foreground/ifar'][:] | ||
| events_to_read = np.count_nonzero(event_ifars > ifar_limit) | ||
| # Sort by IFAR, descending | ||
| event_idx = event_ifars.argsort()[::-1][:events_to_read] | ||
| # Times and tids need to be reset for this set of events: | ||
| times = {} | ||
| tids = {} | ||
| bank_ids = {} | ||
|
|
||
| ifo_list = f.attrs['ifos'].split(' ') | ||
| for ifo in ifo_list: | ||
| times[ifo] = f[f'foreground/{ifo}/time'][:][event_idx] | ||
| tids[ifo] = f[f'foreground/{ifo}/trigger_id'][:][event_idx] | ||
| bank_ids = f['foreground/template_id'][:][event_idx] | ||
|
|
||
| for curr_idx in range(event_idx.size): | ||
| params = mini.get_single_template_params( | ||
| curr_idx, | ||
| times, | ||
| bank_data, | ||
| bank_ids[curr_idx], | ||
| fsdt, | ||
| tids | ||
| ) | ||
| # Extract approximant | ||
| appx = params['approximant'] | ||
| del params['approximant'] | ||
|
|
||
| channel_name = "" | ||
| for ifo in ifo_list: | ||
| ifo_chname = resolve_td_option( | ||
| channel_opts[ifo], | ||
| segments.segment(params['mean_time'], params['mean_time']) | ||
| ) | ||
| channel_name += ifo_chname + " " | ||
|
|
||
| single_temp_files = [] | ||
| for ifo in ifo_list: | ||
| if params['mean_time'] not in insp_analysed_seglists[ifo]: | ||
| logging.info("Mean time %.3f not in segment list", | ||
| params['mean_time']) | ||
| continue | ||
| # Make single-template files to put into the XML file for upload | ||
| single_temp_files += mini.make_single_template_files( | ||
| workflow, | ||
| insp_segs, | ||
| ifo, | ||
| args.inspiral_data_read_name, | ||
| args.inspiral_data_analyzed_name, | ||
| params, | ||
| args.output_dir, | ||
| store_file=True, | ||
| tags=args.tags+['upload', str(curr_idx)], | ||
| ) | ||
|
|
||
| mini.make_upload_files( | ||
| workflow, | ||
| psd_files, | ||
| single_temp_files, | ||
| xml_all, | ||
| curr_idx, | ||
| appx, | ||
| args.output_dir, | ||
| channel_name, | ||
| tags=args.tags+['upload', str(curr_idx)] | ||
| ) | ||
|
|
||
| workflow.save() |
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