def setup_psd_pregenerated(workflow, tags=None):
'''
Setup CBC workflow to use pregenerated psd files.
The file given in cp.get('workflow','pregenerated-psd-file-(ifo)') will
be used as the --psd-file argument to geom_nonspinbank, geom_aligned_bank
and pycbc_plot_psd_file.
Parameters
----------
workflow: pycbc.workflow.core.Workflow
An instanced class that manages the constructed workflow.
tags : list of strings
If given these tags are used to uniquely name and identify output files
that would be produced in multiple calls to this function.
Returns
--------
psd_files : pycbc.workflow.core.FileList
The FileList holding the gating files
'''
if tags is None:
tags = []
psd_files = FileList([])
cp = workflow.cp
global_seg = workflow.analysis_time
file_attrs = {'segs': global_seg, 'tags': tags}
# Check for one psd for all ifos
try:
pre_gen_file = cp.get_opt_tags('workflow-psd',
'psd-pregenerated-file', tags)
file_attrs['ifos'] = workflow.ifos
curr_file = resolve_url_to_file(pre_gen_file, attrs=file_attrs)
psd_files.append(curr_file)
except ConfigParser.Error:
# Check for one psd per ifo
for ifo in workflow.ifos:
try:
pre_gen_file = cp.get_opt_tags('workflow-psd',
'psd-pregenerated-file-%s' % ifo.lower(),
tags)
file_attrs['ifos'] = [ifo]
curr_file = resolve_url_to_file(pre_gen_file, attrs=file_attrs)
psd_files.append(curr_file)
except ConfigParser.Error:
# It's unlikely, but not impossible, that only some ifos
# will have pregenerated PSDs
logging.warn("No psd file specified for IFO %s." % (ifo,))
pass
return psd_files
def get_ipn_sky_files(workflow, file_url, tags=None):
'''
Retreive the sky point files for searching over the IPN error box and
populating it with injections.
Parameters
----------
workflow: pycbc.workflow.core.Workflow
An instanced class that manages the constructed workflow.
file_url : string
The URL of the IPN sky points file.
tags : list of strings
If given these tags are used to uniquely name and identify output files
that would be produced in multiple calls to this function.
Returns
--------
sky_points_file : pycbc.workflow.core.File
File object representing the IPN sky points file.
'''
tags = tags or []
file_attrs = {
'ifos': workflow.ifos,
'segs': workflow.analysis_time,
'exe_name': "IPN_SKY_POINTS",
'tags': tags
}
sky_points_file = resolve_url_to_file(file_url, attrs=file_attrs)
return sky_points_file
def build_veto_filelist(workflow):
"""Construct a FileList instance containing all veto xml files"""
veto_dir = workflow.cp.get('workflow', 'veto-directory')
veto_files = glob.glob(veto_dir + '/*CAT*.xml')
veto_files = [resolve_url_to_file(vf) for vf in veto_files]
veto_files = _workflow.FileList(veto_files)
return veto_files
def build_segment_filelist(workflow):
"""Construct a FileList instance containing all segments txt files"""
seg_dir = workflow.cp.get('workflow', 'segment-dir')
file_names = ["bufferSeg.txt", "offSourceSeg.txt", "onSourceSeg.txt"]
seg_files = [os.path.join(seg_dir, file_name) for file_name in file_names]
seg_files = [resolve_url_to_file(sf) for sf in seg_files]
seg_files = _workflow.FileList(seg_files)
return seg_files
def setup_injection_workflow(workflow,
output_dir=None,
inj_section_name='injections',
exttrig_file=None,
tags=None):
"""
This function is the gateway for setting up injection-generation jobs in a
workflow. It should be possible for this function to support a number
of different ways/codes that could be used for doing this, however as this
will presumably stay as a single call to a single code (which need not be
inspinj) there are currently no subfunctions in this moudle.
Parameters
-----------
workflow : pycbc.workflow.core.Workflow
The Workflow instance that the coincidence jobs will be added to.
output_dir : path
The directory in which injection files will be stored.
inj_section_name : string (optional, default='injections')
The string that corresponds to the option describing the exe location
in the [executables] section of the .ini file and that corresponds to
the section (and sub-sections) giving the options that will be given to
the code at run time.
tags : list of strings (optional, default = [])
A list of the tagging strings that will be used for all jobs created
by this call to the workflow. This will be used in output names.
Returns
--------
inj_files : pycbc.workflow.core.FileList
The list of injection files created by this call.
inj_tags : list of strings
The tag corresponding to each injection file and used to uniquely
identify them. The FileList class contains functions to search
based on tags.
"""
if tags is None:
tags = []
logging.info("Entering injection module.")
make_analysis_dir(output_dir)
# Get full analysis segment for output file naming
full_segment = workflow.analysis_time
ifos = workflow.ifos
# Identify which injections to do by presence of sub-sections in
# the configuration file
inj_tags = []
inj_files = FileList([])
for section in workflow.cp.get_subsections(inj_section_name):
inj_tag = section.upper()
curr_tags = tags + [inj_tag]
# Parse for options in ini file
injection_method = workflow.cp.get_opt_tags("workflow-injections",
"injections-method",
curr_tags)
if injection_method in ["IN_WORKFLOW", "AT_RUNTIME"]:
# FIXME: Add ability to specify different exes
inj_job = LalappsInspinjExecutable(workflow.cp,
inj_section_name,
out_dir=output_dir,
ifos='HL',
tags=curr_tags)
node = inj_job.create_node(full_segment)
if injection_method == "AT_RUNTIME":
workflow.execute_node(node)
else:
workflow.add_node(node)
inj_file = node.output_files[0]
inj_files.append(inj_file)
elif injection_method == "PREGENERATED":
file_attrs = {
'ifos': ['HL'],
'segs': full_segment,
'tags': curr_tags
}
injection_path = workflow.cp.get_opt_tags(
"workflow-injections", "injections-pregenerated-file",
curr_tags)
curr_file = resolve_url_to_file(injection_path, attrs=file_attrs)
inj_files.append(curr_file)
elif injection_method in ["IN_COH_PTF_WORKFLOW", "AT_COH_PTF_RUNTIME"]:
inj_job = LalappsInspinjExecutable(workflow.cp,
inj_section_name,
out_dir=output_dir,
ifos=ifos,
tags=curr_tags)
node = inj_job.create_node(full_segment, exttrig_file)
if injection_method == "AT_COH_PTF_RUNTIME":
workflow.execute_node(node)
else:
workflow.add_node(node)
inj_file = node.output_files[0]
if workflow.cp.has_option("workflow-injections", "em-bright-only"):
em_filter_job = PycbcDarkVsBrightInjectionsExecutable(
workflow.cp,
'em_bright_filter',
tags=curr_tags,
out_dir=output_dir,
ifos=ifos)
node = em_filter_job.create_node(inj_file, full_segment,
curr_tags)
if injection_method == "AT_COH_PTF_RUNTIME":
workflow.execute_node(node)
else:
workflow.add_node(node)
inj_file = node.output_files[0]
if workflow.cp.has_option("workflow-injections",
"do-jitter-skyloc"):
jitter_job = LigolwCBCJitterSkylocExecutable(
workflow.cp,
'jitter_skyloc',
tags=curr_tags,
out_dir=output_dir,
ifos=ifos)
node = jitter_job.create_node(inj_file, full_segment,
curr_tags)
if injection_method == "AT_COH_PTF_RUNTIME":
workflow.execute_node(node)
else:
workflow.add_node(node)
inj_file = node.output_files[0]
if workflow.cp.has_option("workflow-injections",
"do-align-total-spin"):
align_job = LigolwCBCAlignTotalSpinExecutable(
workflow.cp,
'align_total_spin',
tags=curr_tags,
out_dir=output_dir,
ifos=ifos)
node = align_job.create_node(inj_file, full_segment, curr_tags)
if injection_method == "AT_COH_PTF_RUNTIME":
workflow.execute_node(node)
else:
workflow.add_node(node)
inj_file = node.output_files[0]
inj_files.append(inj_file)
else:
err = "Injection method must be one of IN_WORKFLOW, "
err += "AT_RUNTIME or PREGENERATED. Got %s." % (injection_method)
raise ValueError(err)
inj_tags.append(inj_tag)
logging.info("Leaving injection module.")
return inj_files, inj_tags
def setup_tmpltbank_pregenerated(workflow, tags=None):
'''
Setup CBC workflow to use a pregenerated template bank.
The bank given in cp.get('workflow','pregenerated-template-bank') will be used
as the input file for all matched-filtering jobs. If this option is
present, workflow will assume that it should be used and not generate
template banks within the workflow.
Parameters
----------
workflow: pycbc.workflow.core.Workflow
An instanced class that manages the constructed workflow.
tags : list of strings
If given these tags are used to uniquely name and identify output files
that would be produced in multiple calls to this function.
Returns
--------
tmplt_banks : pycbc.workflow.core.FileList
The FileList holding the details of the template bank.
'''
if tags is None:
tags = []
# Currently this uses the *same* fixed bank for all ifos.
# Maybe we want to add capability to analyse separate banks in all ifos?
# Set up class for holding the banks
tmplt_banks = FileList([])
cp = workflow.cp
global_seg = workflow.analysis_time
file_attrs = {'segs': global_seg, 'tags': tags}
try:
# First check if we have a bank for all ifos
pre_gen_bank = cp.get_opt_tags('workflow-tmpltbank',
'tmpltbank-pregenerated-bank', tags)
file_attrs['ifos'] = workflow.ifos
curr_file = resolve_url_to_file(pre_gen_bank, attrs=file_attrs)
tmplt_banks.append(curr_file)
except ConfigParser.Error:
# Okay then I must have banks for each ifo
for ifo in workflow.ifos:
try:
pre_gen_bank = cp.get_opt_tags(
'workflow-tmpltbank',
'tmpltbank-pregenerated-bank-%s' % ifo.lower(), tags)
file_attrs['ifos'] = [ifo]
curr_file = resolve_url_to_file(pre_gen_bank, attrs=file_attrs)
tmplt_banks.append(curr_file)
except ConfigParser.Error:
err_msg = "Cannot find pregerated template bank in section "
err_msg += "[workflow-tmpltbank] or any tagged sections. "
if tags:
tagged_secs = " ".join("[workflow-tmpltbank-%s]" \
%(ifo,) for ifo in workflow.ifos)
err_msg += "Tagged sections are %s. " % (tagged_secs, )
err_msg += "I looked for 'tmpltbank-pregenerated-bank' option "
err_msg += "and 'tmpltbank-pregenerated-bank-%s'." % (ifo, )
raise ConfigParser.Error(err_msg)
return tmplt_banks
def setup_foreground_minifollowups(workflow,
coinc_file,
single_triggers,
tmpltbank_file,
insp_segs,
insp_data_name,
insp_anal_name,
dax_output,
out_dir,
tags=None):
""" Create plots that followup the Nth loudest coincident injection
from a statmap produced HDF file.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
coinc_file:
single_triggers: list of pycbc.workflow.File
A list cointaining the file objects associated with the merged
single detector trigger files for each ifo.
tmpltbank_file: pycbc.workflow.File
The file object pointing to the HDF format template bank
insp_segs: SegFile
The segment file containing the data read and analyzed by each inspiral
job.
insp_data_name: str
The name of the segmentlist storing data read.
insp_anal_name: str
The name of the segmentlist storing data analyzed.
out_dir: path
The directory to store minifollowups result plots and files
tags: {None, optional}
Tags to add to the minifollowups executables
Returns
-------
layout: list
A list of tuples which specify the displayed file layout for the
minifollops plots.
"""
logging.info('Entering minifollowups module')
if not workflow.cp.has_section('workflow-minifollowups'):
logging.info(
'There is no [workflow-minifollowups] section in configuration file'
)
logging.info('Leaving minifollowups')
return
tags = [] if tags is None else tags
makedir(dax_output)
# turn the config file into a File class
config_path = os.path.abspath(dax_output + '/' + '_'.join(tags) +
'foreground_minifollowup.ini')
workflow.cp.write(open(config_path, 'w'))
config_file = resolve_url_to_file(config_path)
exe = Executable(workflow.cp,
'foreground_minifollowup',
ifos=workflow.ifos,
out_dir=dax_output,
tags=tags)
node = exe.create_node()
node.add_input_opt('--config-files', config_file)
node.add_input_opt('--bank-file', tmpltbank_file)
node.add_input_opt('--statmap-file', coinc_file)
node.add_multiifo_input_list_opt('--single-detector-triggers',
single_triggers)
node.add_input_opt('--inspiral-segments', insp_segs)
node.add_opt('--inspiral-data-read-name', insp_data_name)
node.add_opt('--inspiral-data-analyzed-name', insp_anal_name)
if tags:
node.add_list_opt('--tags', tags)
node.new_output_file_opt(workflow.analysis_time, '.dax', '--dax-file')
node.new_output_file_opt(workflow.analysis_time, '.dax.map',
'--output-map')
name = node.output_files[0].name
map_file = node.output_files[1]
node.add_opt('--workflow-name', name)
node.add_opt('--output-dir', out_dir)
workflow += node
# execute this in a sub-workflow
fil = node.output_files[0]
# determine if a staging site has been specified
job = SubWorkflow(fil.name, is_planned=False)
input_files = [tmpltbank_file, coinc_file, insp_segs] + single_triggers
job.add_inputs(*input_files)
job.set_subworkflow_properties(map_file,
staging_site=workflow.staging_site,
cache_file=workflow.cache_file)
job.add_into_workflow(workflow, parents=[node])
logging.info('Leaving minifollowups module')
def setup_single_det_minifollowups(workflow,
single_trig_file,
tmpltbank_file,
insp_segs,
insp_data_name,
insp_anal_name,
dax_output,
out_dir,
veto_file=None,
veto_segment_name=None,
statfiles=None,
tags=None):
""" Create plots that followup the Nth loudest clustered single detector
triggers from a merged single detector trigger HDF file.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
single_trig_file: pycbc.workflow.File
The File class holding the single detector triggers.
tmpltbank_file: pycbc.workflow.File
The file object pointing to the HDF format template bank
insp_segs: SegFile
The segment file containing the data read by each inspiral job.
insp_data_name: str
The name of the segmentlist storing data read.
insp_anal_name: str
The name of the segmentlist storing data analyzed.
out_dir: path
The directory to store minifollowups result plots and files
statfiles: FileList (optional, default=None)
Supplementary files necessary for computing the single-detector
statistic.
tags: {None, optional}
Tags to add to the minifollowups executables
Returns
-------
layout: list
A list of tuples which specify the displayed file layout for the
minifollops plots.
"""
logging.info('Entering minifollowups module')
if not workflow.cp.has_section('workflow-sngl_minifollowups'):
msg = 'There is no [workflow-sngl_minifollowups] section in '
msg += 'configuration file'
logging.info(msg)
logging.info('Leaving minifollowups')
return
tags = [] if tags is None else tags
makedir(dax_output)
# turn the config file into a File class
curr_ifo = single_trig_file.ifo
config_path = os.path.abspath(dax_output + '/' + curr_ifo + \
'_'.join(tags) + 'singles_minifollowup.ini')
workflow.cp.write(open(config_path, 'w'))
config_file = resolve_url_to_file(config_path)
exe = Executable(workflow.cp,
'singles_minifollowup',
ifos=curr_ifo,
out_dir=dax_output,
tags=tags)
node = exe.create_node()
node.add_input_opt('--config-files', config_file)
node.add_input_opt('--bank-file', tmpltbank_file)
node.add_input_opt('--single-detector-file', single_trig_file)
node.add_input_opt('--inspiral-segments', insp_segs)
node.add_opt('--inspiral-data-read-name', insp_data_name)
node.add_opt('--inspiral-data-analyzed-name', insp_anal_name)
node.add_opt('--instrument', curr_ifo)
if veto_file is not None:
assert (veto_segment_name is not None)
node.add_input_opt('--veto-file', veto_file)
node.add_opt('--veto-segment-name', veto_segment_name)
if statfiles:
statfiles = statfiles.find_output_with_ifo(curr_ifo)
node.add_input_list_opt('--statistic-files', statfiles)
if tags:
node.add_list_opt('--tags', tags)
node.new_output_file_opt(workflow.analysis_time, '.dax', '--dax-file')
node.new_output_file_opt(workflow.analysis_time, '.dax.map',
'--output-map')
name = node.output_files[0].name
map_file = node.output_files[1]
node.add_opt('--workflow-name', name)
node.add_opt('--output-dir', out_dir)
workflow += node
# execute this in a sub-workflow
fil = node.output_files[0]
job = SubWorkflow(fil.name, is_planned=False)
input_files = [tmpltbank_file, insp_segs, single_trig_file]
if veto_file is not None:
input_files.append(veto_file)
if statfiles:
input_files += statfiles
job.add_inputs(*input_files)
job.set_subworkflow_properties(map_file,
staging_site=workflow.staging_site,
cache_file=workflow.cache_file)
job.add_into_workflow(workflow, parents=[node])
logging.info('Leaving minifollowups module')
