Revision 095105451a22dd5a59c832656163a2efa462acb4 authored by Duncan Brown on 25 September 2018, 15:06:18 UTC, committed by Collin Capano on 26 October 2018, 14:35:14 UTC
1 parent cf96817
pycbc_optimal_snr
#!/usr/bin/env python
# Copyright (C) 2014 Andrew Lundgren, Tito Dal Canton
#
# 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.
"""
Compute the optimal SNRs for every injection in a sim_inspiral table and
store the result in selectable columns of the same table.
"""
import logging
import argparse
import multiprocessing
import numpy as np
import h5py
import pycbc
import pycbc.inject
import pycbc.psd
from glue.ligolw import utils as ligolw_utils
from pycbc.filter import sigma, make_frequency_series
from pycbc.types import TimeSeries, FrequencySeries, zeros, float32, \
MultiDetOptionAction, load_frequencyseries
from glue.ligolw import lsctables
import pycbc.version
class TimeIndependentPSD(object):
def __init__(self, psd_series):
self.psd_series = psd_series
def __call__(self, time=None):
return self.psd_series
class TimeVaryingPSD(object):
def __init__(self, file_name, length=None, delta_f=None, f_low=None):
f = h5py.File(file_name, 'r')
self.file_name = file_name
detector = f.keys()[0]
self.start_times = f[detector + '/start_time'][:]
self.end_times = f[detector + '/end_time'][:]
self.file_f_low = f.attrs['low_frequency_cutoff']
f.close()
self._curr_psd = {}
self._curr_psd_index = {}
self.detector = detector
self.length = length
self.delta_f = delta_f
self.f_low = f_low
def __call__(self, time=None):
mask = np.logical_and(self.start_times <= time,
self.end_times > time)
if np.count_nonzero(mask) >= 1:
center_times = (self.start_times[mask] + self.end_times[mask]) / 2.
closest_idx = np.argsort(abs(center_times - time))[0]
return self.get_psd(np.flatnonzero(mask)[closest_idx])
else:
return None
def get_psd(self, index):
curr_pid = multiprocessing.current_process().pid
if curr_pid not in self._curr_psd_index.keys():
self._curr_psd_index[curr_pid] = -1
if not index == self._curr_psd_index[curr_pid]:
group = self.detector + '/psds/' + str(index)
psd = load_frequencyseries(self.file_name, group=group)
if delta_f is not None and psd.delta_f != delta_f:
psd = pycbc.psd.interpolate(psd, delta_f)
if self.length is not None and self.length != len(psd):
psd2 = FrequencySeries(zeros(self.length, dtype=psd.dtype),
delta_f=psd.delta_f)
if self.length > len(psd):
psd2[:] = np.inf
psd2[0:len(psd)] = psd
else:
psd2[:] = psd[0:self.length]
psd = psd2
if self.f_low is not None and self.f_low < self.file_f_low:
# avoid using the PSD below the f_low given in the file
k = int(file_f_low / psd.delta_f)
psd[0:k] = np.inf
self._curr_psd[curr_pid] = psd
self._curr_psd_index[curr_pid] = index
return self._curr_psd[curr_pid]
if __name__ == '__main__':
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--version", action=pycbc.version.Version)
parser.add_argument('--input-file', '-i', dest='inj_xml', required=True,
help='Input LIGOLW file defining injections')
parser.add_argument('--output-file', '-o', dest='out_file', required=True,
help='Output LIGOLW file')
parser.add_argument('--f-low', type=float, default=30.,
help='Start frequency of matched-filter integration in Hz (default %(default)s)')
parser.add_argument('--seg-length', type=float, default=256,
help='Segment duration in seconds (default %(default)s)')
parser.add_argument('--sample-rate', type=float, default=16384,
help='Data sample rate in Hz (default %(default)s)')
parser.add_argument('--snr-columns', nargs='+', action=MultiDetOptionAction,
metavar='DETECTOR:COLUMN', required=True,
help='Defines in which column of the sim_inspiral table' \
' the optimal SNR for each detector should be stored.' \
' COLUMN should be an existing sim_inspiral column with ' \
' no useful data in it, good candidates are usually' \
' alpha1, alpha2 etc.')
parser.add_argument('--cores', default=1, type=int,
help='Parallelize the computation over the given '
'number of cores')
parser.add_argument('--ignore-waveform-errors', action='store_true',
help='Ignore errors in waveform generation and keep '
'the corresponding column unchanged')
parser.add_argument('--verbose', action='store_true',
help='Print which injection is going to be attempted '
'next and when it completes. Use this to debug '
'misbehaving approximants which crash or quit '
'the Python interpreter')
parser.add_argument('--progress', action='store_true',
help='Show a progress bar (requires tqdm)')
psd_group = pycbc.psd.insert_psd_option_group_multi_ifo(parser)
psd_group.add_argument('--time-varying-psds', nargs='*', metavar='FILE',
help='Instead of time-independent PSDs, use time-varying '
'PSDs from the given HDF5 files and pick the appropriate '
'PSD for each injection')
opts = parser.parse_args()
detectors = opts.snr_columns.keys()
if not opts.time_varying_psds:
pycbc.psd.verify_psd_options_multi_ifo(opts, parser, detectors)
log_level = logging.DEBUG if opts.verbose else logging.INFO
logging.basicConfig(level=log_level,
format='%(asctime)s %(message)s',
datefmt='%Y-%m-%d %H:%M:%S')
seg_len = opts.seg_length
sample_rate = opts.sample_rate
delta_t = 1. / sample_rate
delta_f = 1. / seg_len
tlen = int(seg_len * sample_rate)
flen = tlen / 2 + 1
f_low = opts.f_low
logging.info("Loading PSDs")
if opts.time_varying_psds:
psds = {}
for tvpsd_file in opts.time_varying_psds:
tvpsd = TimeVaryingPSD(tvpsd_file, flen, delta_f, f_low)
psds[tvpsd.detector] = tvpsd
if set(detectors) != set(psds.keys()):
parser.error('Inconsistent detector list in time-varying PSD ' \
'specification (%s vs %s)' % (detectors, psds.keys()))
else:
psds = pycbc.psd.from_cli_multi_ifos(
opts,
length_dict=dict((det, flen) for det in detectors),
delta_f_dict=dict((det, delta_f) for det in detectors),
low_frequency_cutoff_dict=dict((det, f_low) for det in detectors),
ifos=detectors,
strain_dict=dict((det, None) for det in detectors),
dyn_range_factor=pycbc.DYN_RANGE_FAC)
for det in detectors:
psds[det] = TimeIndependentPSD(psds[det].astype(float32))
def get_injection(injections, det, injection_time, simulation_id):
""" Do an injection from the injection XML file, specified by
IFO and end time"""
# leave 4 s of padding at the end for possible ringdown
start_time = int(injection_time + 4. - seg_len)
strain = TimeSeries(zeros(tlen, dtype=float32), delta_t=delta_t,
epoch=start_time)
injections.apply(strain, det, distance_scale=1./pycbc.DYN_RANGE_FAC,
simulation_ids=[simulation_id])
return make_frequency_series(strain)
def compute_optimal_snr(inj, return_found=False):
for det, column in opts.snr_columns.items():
# geocent time is robust to potentially incomplete sim tables
injection_time = inj.geocent_end_time
psd = psds[det](injection_time)
if psd is None:
continue
logging.debug('Trying injection %s', inj.simulation_id)
try:
wave = get_injection(injections, det, injection_time,
simulation_id=inj.simulation_id)
except Exception, e:
if opts.ignore_waveform_errors:
logging.warn('%s: waveform generation failed, skipping (%s)',
inj.simulation_id, e)
continue
else:
logging.error('%s: waveform generation failed with the '
'following exception', inj.simulation_id)
raise
logging.debug('Injection %s completed', inj.simulation_id)
sval = sigma(wave, psd=psd, low_frequency_cutoff=f_low)
setattr(inj, column, sval)
if return_found:
# No need to do any other dets if we just
# want to trigger weave
return (inj, True)
if return_found:
return (inj, False)
return inj
logging.info("Loading injections")
injections = pycbc.inject.InjectionSet(opts.inj_xml)
np.random.seed(100)
inj_table = sorted(injections.table, key=lambda x: np.random.random())
out_sim_inspiral = lsctables.New(lsctables.SimInspiralTable,
columns=injections.table.columnnames)
logging.info('Starting workers')
pool = multiprocessing.Pool(processes=opts.cores)
progress = lambda x, **kwargs: x
if opts.progress:
try:
from tqdm import tqdm as progress
except ImportError:
logging.warn('cannot import tqdm; not showing progress bar')
pass
for inj in progress(pool.imap(compute_optimal_snr, inj_table),
total=len(inj_table)):
out_sim_inspiral.append(inj)
out_sim_inspiral.sort(key=lambda x: x.geocent_end_time)
logging.info('Writing output')
llw_doc = injections.indoc
llw_root = llw_doc.childNodes[0]
llw_root.removeChild(injections.table)
llw_root.appendChild(out_sim_inspiral)
ligolw_utils.write_filename\
(llw_doc, opts.out_file, gz=opts.out_file.endswith('gz'))
logging.info('Done')
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