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Update pycbc_brute_bank to include option to cut wavelength and save … #4506

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merged 12 commits into from
Oct 25, 2023
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Merged

Update pycbc_brute_bank to include option to cut wavelength and save … #4506

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Update pycbc_brute_bank to include option to cut wavelength and save …
kkacanja Sep 26, 2023
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kkacanja Sep 27, 2023
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Update pycbc_brute_bank
kkacanja Sep 29, 2023
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Update pycbc_brute_bank
kkacanja Sep 29, 2023
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Update pycbc_brute_bank
kkacanja Oct 10, 2023
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Update pycbc_brute_bank
kkacanja Oct 10, 2023
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Update pycbc_brute_bank
kkacanja Oct 24, 2023
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Merge branch 'gwastro:master' into kkacanja-patch-1
kkacanja Oct 24, 2023
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Update pycbc_brute_bank
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kkacanja Oct 25, 2023
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42 changes: 27 additions & 15 deletions bin/bank/pycbc_brute_bank
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Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,9 @@ parser.add_argument('--minimal-match', default=0.97, type=float)
parser.add_argument('--buffer-length', default=2, type=float,
help='size of waveform buffer in seconds')
parser.add_argument('--cut-wavelength', type=bool,
help="Option to cut the wavelength")
help="When enabled, the program will adjust the wavelength to fit the specified length in max-signal-length ")
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We could probably combine these two options, so if max-signal-length isn't given, it doesn't impose any cut.

parser.add_argument('--max-signal-length', type= float,
help="maximum length of the waveform model")
parser.add_argument('--sample-rate', default=2048, type=float,
help='sample rate in seconds')
parser.add_argument('--low-frequency-cutoff', default=20.0, type=float)
Expand Down Expand Up @@ -273,31 +275,35 @@ class GenUniformWaveform(object):

def generate(self, **kwds):
kwds.update(fdict)
import numpy
from pycbc.waveform.spa_tmplt import spa_length_in_time
flow = numpy.arange(self.f_lower, 100, .1)[::-1]
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This line and the next should probably be within the if statement.

maxlen = args.max_signal_length
length = spa_length_in_time(mass1=kwds['mass1'], mass2=kwds['mass2'], f_lower=flow, phase_order=-1)

x = numpy.searchsorted(length, maxlen) - 1
l = length[x]
f = flow[x]
if kwds['approximant'] in pycbc.waveform.fd_approximants():
if args.cut_wavelength:
import numpy
from pycbc.waveform.spa_tmplt import spa_length_in_time
flow = numpy.arange(self.f_lower, 100, .1)[::-1]
maxlen = 512
length = spa_length_in_time(mass1=kwds['mass1'], mass2=kwds['mass2'], f_lower=flow, phase_order=-1)

x = numpy.searchsorted(length, maxlen) - 1
l = length[x]
f = flow[x]
#logging.info("cut wavelength is specified")
hp, hc = pycbc.waveform.get_fd_waveform(delta_f=self.delta_f,
f_lower=f, f_ref=10.0, **kwds)
kwds['flow'] = f
kwds['f_lower'] = f

if 'fratio' in kwds:
hp = hc * kwds['fratio'] + hp * (1 - kwds['fratio'])

else:
import numpy
kwds.update(fdict)
#import numpy
#logging.info("cut wavelength not specified")
ws = pycbc.waveform.get_fd_waveform(delta_f=self.delta_f,
f_lower=self.f_lower, **kwds)
hp = ws[0]
hc = ws[1]

kwds['f_lower'] = self.f_lower

if 'fratio' in kwds:
hp = hc * kwds['fratio'] + hp * (1 - kwds['fratio'])
else:
Expand Down Expand Up @@ -447,6 +453,8 @@ def cdraw(rtype, ts, te):

tau0s = args.tau0_start
tau0e = tau0s + args.tau0_crawl
# total_it = args.tau0_crawl/(args.tau0_end - tau0s)
# completed_iterations = 0
go = True

region = 0
Expand All @@ -469,6 +477,7 @@ while tau0s < args.tau0_end:
if r > 10:
conv = uconv
kloop = 0

while ((kloop == 0) or (kconv / okconv) > .5) and len(bank) > 10:
r += 1
kloop += 1
Expand All @@ -477,9 +486,13 @@ while tau0s < args.tau0_end:
bank, kconv = bank.check_params(gen, params, args.minimal_match)
logging.info("%s: Round (K) (%s): %s Size: %s conv: %s added: %s",
region, kloop, r, len(bank), kconv, len(bank) - blen)

# completed_iterations += 1
# progress_percentage = completed_iterations / total_it

if uconv:
logging.info('Ratio of convergences: %2.3f' % (kconv / (uconv)))
logging.info('Progress: {:.0%} completed'.format(tau0s/args.tau0_end))
logging.info('Progress: {:.0%} completed'.format(tau0e/args.tau0_end))

if kloop == 1:
okconv = kconv
Expand All @@ -500,4 +513,3 @@ for k in bank.keys():
if val.dtype.char == 'U':
val = val.astype('bytes')
o[k] = val
o['f_lower'] = numpy.ones(len(val)) * args.low_frequency_cutoff