codes in bin

bin/pycbc_banksim_combine_banks

@@ -22,10 +22,8 @@ files. It is assumed that input files have analysed the same set of injections.
 Concatenation of injections is done separately.
 """
 
-from os.path import isfile
 import argparse
-import logging
-from numpy import *
+from numpy import dtype, array
 
 import pycbc
 

bin/pycbc_banksim_skymax

@@ -17,24 +17,23 @@
 """Calculate the fitting factors of simulated signals with a template bank."""
 
 
-import sys
 import logging
-from numpy import complex64, float32, sqrt, argmax, real, array
+from numpy import complex64, sqrt, argmax, real, array
 from argparse import ArgumentParser
 from math import ceil, log
 from tqdm import tqdm
 
 from ligo.lw import utils as ligolw_utils
 from ligo.lw import lsctables
 
-from pycbc.pnutils import mass1_mass2_to_mchirp_eta, f_SchwarzISCO
+from pycbc.pnutils import mass1_mass2_to_mchirp_eta
 from pycbc.pnutils import nearest_larger_binary_number
 from pycbc.pnutils import mass1_mass2_to_tau0_tau3
 from pycbc.waveform import get_td_waveform, get_fd_waveform, td_approximants, fd_approximants
 from pycbc.waveform.utils import taper_timeseries
 from pycbc import DYN_RANGE_FAC
-from pycbc.types import FrequencySeries, TimeSeries, zeros, real_same_precision_as, complex_same_precision_as
-from pycbc.filter import match, sigmasq, resample_to_delta_t
+from pycbc.types import FrequencySeries, TimeSeries, zeros, complex_same_precision_as
+from pycbc.filter import sigmasq
 from pycbc.filter import overlap_cplx, matched_filter
 from pycbc.filter import compute_max_snr_over_sky_loc_stat
 from pycbc.filter import compute_max_snr_over_sky_loc_stat_no_phase

bin/pycbc_compress_bank

@@ -28,17 +28,12 @@ hdf file."""
 
 import argparse
 import numpy
-import h5py
 import logging
 
 import pycbc
-from pycbc import psd, DYN_RANGE_FAC
 from pycbc.waveform import compress
 from pycbc import waveform
 from pycbc.types import FrequencySeries, real_same_precision_as
-from pycbc import pnutils
-from pycbc import filter
-
 
 parser = argparse.ArgumentParser(description=__description__)
 pycbc.add_common_pycbc_options(parser)

bin/pycbc_convertinjfiletohdf

@@ -25,8 +25,7 @@ import numpy
 import shutil
 
 import pycbc
-from pycbc.inject import InjectionSet, CBCHDFInjectionSet
-from pycbc.types import float64, float32
+from pycbc.inject import CBCHDFInjectionSet
 from pycbc.io.record import FieldArray
 from pycbc.io.hdf import HFile
 

bin/pycbc_create_injections

@@ -113,16 +113,13 @@ import sys
 import argparse
 import logging
 import numpy
-import h5py
 from numpy.random import uniform
 
 import pycbc
 from pycbc.inject import InjectionSet
 from pycbc import distributions
 from pycbc import transforms
 from pycbc.distributions import JointDistribution
-from pycbc.io import record
-from pycbc.waveform import parameters
 from pycbc.workflow import configuration
 from pycbc.workflow import WorkflowConfigParser
 

bin/pycbc_data_store

@@ -3,7 +3,6 @@
 """
 import logging
 import argparse
-import numpy
 
 import pycbc
 import pycbc.strain

bin/pycbc_faithsim_collect_results

@@ -8,7 +8,7 @@ computing the match between them and creating a .dat file with the results.
 import argparse
 import numpy as np
 
-from ligo.lw import utils, table, lsctables
+from ligo.lw import utils, lsctables
 
 from pycbc import add_common_pycbc_options, init_logging
 from pycbc.io.ligolw import LIGOLWContentHandler

bin/pycbc_get_ffinal

@@ -7,14 +7,13 @@ the duration of time domain waveforms.
 __prog__ = 'pycbc_get_ffinal'
 __author__ = 'Collin Capano <[email protected]>'
 
-import os, sys
+import sys
 import numpy
 import argparse
 
 import pycbc
 from pycbc import waveform
 
-from ligo.lw import lsctables
 from ligo.lw import utils as ligolw_utils
 from ligo.lw import table
 from ligo.lw.utils import process

bin/pycbc_hdf5_splitbank

@@ -23,7 +23,6 @@ smaller banks where the number of smaller banks is a user input
 
 import argparse
 import numpy
-import h5py
 import logging
 from numpy import random
 
@@ -92,7 +91,6 @@ if args.random_sort:
     tmplt_bank.table = templates
 
 if args.mchirp_sort:
-    from pycbc import pnutils
     mcsort = numpy.argsort(templates.mchirp)
     templates = templates[mcsort]
     tmplt_bank.table = templates

bin/pycbc_inspiral

@@ -22,15 +22,14 @@ import copy
 import logging
 import argparse
 import numpy
-import itertools
 import time
 from pycbc.pool import BroadcastPool as Pool
 
 import pycbc
 from pycbc import vetoes, psd, waveform, strain, scheme, fft, DYN_RANGE_FAC, events
 from pycbc.vetoes.sgchisq import SingleDetSGChisq
-from pycbc.filter import MatchedFilterControl, make_frequency_series, qtransform
-from pycbc.types import TimeSeries, FrequencySeries, zeros, float32, complex64
+from pycbc.filter import MatchedFilterControl, qtransform
+from pycbc.types import zeros, float32, complex64
 import pycbc.opt
 import pycbc.inject
 

bin/pycbc_inspiral_skymax

@@ -24,8 +24,8 @@ import numpy
 from pycbc import vetoes, psd, waveform, events, strain, scheme, fft
 from pycbc.vetoes.sgchisq import SingleDetSGChisq
 from pycbc import DYN_RANGE_FAC
-from pycbc.filter import MatchedFilterSkyMaxControl, make_frequency_series, MatchedFilterSkyMaxControlNoPhase
-from pycbc.types import TimeSeries, FrequencySeries, zeros, float32, complex64
+from pycbc.filter import MatchedFilterSkyMaxControl, MatchedFilterSkyMaxControlNoPhase
+from pycbc.types import zeros, float32, complex64
 import pycbc.fft.fftw
 import pycbc.opt
 

bin/pycbc_live

@@ -10,12 +10,11 @@ launched with mpirun.
 See https://arxiv.org/abs/1805.11174 for an overview."""
 
 import sys
-import argparse, numpy, pycbc, logging, cProfile, h5py, lal, json
+import argparse, numpy, pycbc, logging, cProfile, h5py, json
 import os.path
 import itertools
 import platform
 import subprocess
-import multiprocessing
 from multiprocessing.dummy import threading
 from matplotlib import use
 use('agg')
@@ -43,7 +42,6 @@ from pycbc.detector import ppdets
 from pycbc.filter import resample
 from pycbc.psd import estimate
 from pycbc.psd import variation
-from pycbc.live import snr_optimizer
 from pycbc import conversions as conv
 
 # Use cached class-based FFTs in the resample and estimate module

bin/pycbc_make_faithsim

@@ -52,7 +52,6 @@ def mkdir(dir_name):
         pass
 
 def matches_in_list(slist, match):
-    import re
     matches = []
     for st in slist:
         if st.startswith(match):

bin/pycbc_make_html_page

@@ -19,17 +19,13 @@
 import argparse
 import os
 import stat
-import random
 import shutil
 import zipfile
 import codecs
 from jinja2 import Environment, FileSystemLoader
 
-import igwn_segments as segments
-
 import pycbc.results
 from pycbc.results.render import get_embedded_config, render_workflow_html_template, setup_template_render
-from pycbc.workflow import segment
 
 def examine_dir(cwd):
     """

bin/pycbc_make_skymap

@@ -18,14 +18,13 @@ from matplotlib import use as mpl_use_backend
 mpl_use_backend('agg')
 
 import numpy as np
-import h5py
 
 from ligo.gracedb.rest import GraceDb
 
 import pycbc
 from pycbc.filter import sigmasq
 from pycbc.io import gracedb as pycbc_gracedb, WaveformArray
-from pycbc.types import (TimeSeries, FrequencySeries, load_timeseries,
+from pycbc.types import (load_timeseries,
                          load_frequencyseries, MultiDetMultiColonOptionAction,
                          MultiDetOptionAction, MultiDetOptionAppendAction)
 from pycbc.pnutils import nearest_larger_binary_number
@@ -605,4 +604,4 @@ if __name__ == '__main__':
          segment_source=opt.segment_source, segment_server=opt.segment_server,
          veto_definer=opt.veto_definer, injection_file=opt.injection_file, 
          fake_strain=opt.fake_strain, fake_strain_from_file=opt.fake_strain_from_file, fake_strain_seed=opt.fake_strain_seed,
-         rescale_loglikelihood=opt.rescale_loglikelihood)
+         rescale_loglikelihood=opt.rescale_loglikelihood)

bin/pycbc_merge_inj_hdf

@@ -23,7 +23,6 @@ Merge hdf injection files
 import logging
 import argparse
 import numpy as np
-import h5py
 
 import pycbc
 import pycbc.inject

bin/pycbc_multi_inspiral

@@ -44,7 +44,6 @@ from pycbc import (
     add_common_pycbc_options,
 )
 from pycbc.events import ranking, coherent as coh, EventManagerCoherent
-from pycbc.io.hdf import HFile
 from pycbc.filter import MatchedFilterControl
 from pycbc.types import zeros, float32, complex64, angle_as_radians
 from pycbc.vetoes import sgchisq

bin/pycbc_randomize_inj_dist_by_optsnr

@@ -13,7 +13,6 @@ from argparse import ArgumentParser
 
 from ligo.lw import lsctables
 from ligo.lw import utils as ligolw_utils
-from ligo.lw import table
 
 import pycbc
 from pycbc.io.ligolw import LIGOLWContentHandler

bin/pycbc_source_probability_offline

@@ -3,7 +3,6 @@
 Compute source probabilities using mchirp estimation method for all events
 in a chunk with an IFAR above certain threshold.
 """
-import h5py
 import json
 import tqdm
 import argparse