def make_trigger_timeseries(workflow,
singles,
ifo_times,
out_dir,
special_tids=None,
exclude=None,
require=None,
tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'plot_trigger_timeseries'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
node = PlotExecutable(workflow.cp,
name,
ifos=workflow.ifos,
out_dir=out_dir,
tags=[tag] + tags).create_node()
node.add_multiifo_input_list_opt('--single-trigger-files', singles)
node.add_opt('--times', ifo_times)
node.new_output_file_opt(workflow.analysis_time, '.png',
'--output-file')
if special_tids is not None:
node.add_opt('--special-trigger-ids', special_tids)
workflow += node
files += node.output_files
return files
def make_inference_corner_plot(workflow, mcmc_file, output_dir, config_file,
name="mcmc_corner", analysis_seg=None, tags=None):
""" Sets up the corner plot of the posteriors in the workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
mcmc_file: pycbc.workflow.File
The file with MCMC samples.
output_dir: str
The directory to store result plots and files.
config_file: str
The path to the inference configuration file that has a
[variable_args] section.
name: str
The name in the [executables] section of the configuration file
to use.
analysis_segs: {None, glue.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the minifollowups executables.
Returns
-------
pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# read config file to get variables that vary
cp = WorkflowConfigParser([config_file])
variable_args = cp.options("variable_args")
# add derived mass parameters if mass1 and mass2 in variable_args
if "mass1" in variable_args and "mass2" in variable_args:
variable_args += ["mchirp", "eta"]
# make the directory that will contain the output files
makedir(output_dir)
# make a node for plotting the posterior as a corner plot
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=output_dir, universe="local",
tags=tags).create_node()
# add command line options
node.add_input_opt("--input-file", mcmc_file)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
# add node to workflow
workflow += node
return node.output_files
def make_inference_inj_plots(workflow,
inference_files,
output_dir,
parameters,
name="inference_recovery",
analysis_seg=None,
tags=None):
""" Sets up the recovered versus injected parameter plot in the workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
inference_files: pycbc.workflow.FileList
The files with posterior samples.
output_dir: str
The directory to store result plots and files.
parameters : list
A ``list`` of parameters. Each parameter gets its own plot.
name: str
The name in the [executables] section of the configuration file
to use.
analysis_segs: {None, ligo.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the inference executables.
Returns
-------
pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
output_files = FileList([])
# make the directory that will contain the output files
makedir(output_dir)
# add command line options
for (ii, param) in enumerate(parameters):
plot_exe = PlotExecutable(workflow.cp,
name,
ifos=workflow.ifos,
out_dir=output_dir,
tags=tags + ['param{}'.format(ii)])
node = plot_exe.create_node()
node.add_input_list_opt("--input-file", inference_files)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
node.add_opt("--parameters", param)
workflow += node
output_files += node.output_files
return output_files
def make_trigger_timeseries(workflow,
singles,
ifo_times,
out_dir,
special_tids,
exclude=None,
require=None,
tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'plot_trigger_timeseries'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
node = PlotExecutable(
workflow.cp,
name,
ifos=workflow.ifos,
out_dir=out_dir,
tags=[tag] + tags).create_node()
node.add_multiifo_input_list_opt('--single-trigger-files', singles)
node.add_opt('--times', ifo_times)
node.new_output_file_opt(workflow.analysis_time, '.png',
'--output-file')
if special_tids is not None:
node.add_opt('--special-trigger-ids', special_tids)
workflow += node
files += node.output_files
return files
def make_inference_inj_plots(workflow, inference_files, output_dir,
parameters, name="inference_recovery",
analysis_seg=None, tags=None):
""" Sets up the recovered versus injected parameter plot in the workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
inference_files: pycbc.workflow.FileList
The files with posterior samples.
output_dir: str
The directory to store result plots and files.
parameters : list
A ``list`` of parameters. Each parameter gets its own plot.
name: str
The name in the [executables] section of the configuration file
to use.
analysis_segs: {None, ligo.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the inference executables.
Returns
-------
pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
output_files = FileList([])
# make the directory that will contain the output files
makedir(output_dir)
# add command line options
for (ii, param) in enumerate(parameters):
plot_exe = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=output_dir,
tags=tags+['param{}'.format(ii)])
node = plot_exe.create_node()
node.add_input_list_opt("--input-file", inference_files)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
node.add_opt("--parameters", param)
workflow += node
output_files += node.output_files
return output_files
def make_inference_posterior_plot(workflow,
inference_file,
output_dir,
parameters=None,
name="inference_posterior",
analysis_seg=None,
tags=None):
""" Sets up the corner plot of the posteriors in the workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
inference_file: pycbc.workflow.File
The file with posterior samples.
output_dir: str
The directory to store result plots and files.
parameters : list
A list of parameters to plot.
name: str
The name in the [executables] section of the configuration file
to use.
analysis_segs: {None, ligo.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the inference executables.
Returns
-------
pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# make the directory that will contain the output files
makedir(output_dir)
# make a node for plotting the posterior as a corner plot
node = PlotExecutable(workflow.cp,
name,
ifos=workflow.ifos,
out_dir=output_dir,
universe="local",
tags=tags).create_node()
# add command line options
node.add_input_opt("--input-file", inference_file)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
if parameters is not None:
node.add_opt("--parameters", " ".join(parameters))
# add node to workflow
workflow += node
return node.output_files
def make_inference_samples_plot(workflow,
inference_file,
output_dir,
parameters=None,
name="inference_samples",
analysis_seg=None,
tags=None):
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# make the directory that will contain the output files
makedir(output_dir)
# make a node for plotting the posterior as a corner plot
node = PlotExecutable(workflow.cp,
name,
ifos=workflow.ifos,
out_dir=output_dir,
universe="local",
tags=tags).create_node()
# add command line options
node.add_input_opt("--input-file", inference_file)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
node.add_opt("--parameters", " ".join(parameters))
# add node to workflow
workflow += node
return node.output_files
def make_inj_info(workflow, injection_file, injection_index, num, out_dir,
tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'page_injinfo'
files = FileList([])
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=out_dir, tags=tags).create_node()
node.add_input_opt('--injection-file', injection_file)
node.add_opt('--injection-index', str(injection_index))
node.add_opt('--n-nearest', str(num))
node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
workflow += node
files += node.output_files
return files
def make_inference_acceptance_rate_plot(workflow, mcmc_file, output_dir,
name="mcmc_rate", analysis_seg=None, tags=None):
""" Sets up the acceptance rate plot in the workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
mcmc_file: pycbc.workflow.File
The file with MCMC samples.
output_dir: str
The directory to store result plots and files.
name: str
The name in the [executables] section of the configuration file
to use.
analysis_segs: {None, glue.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the minifollowups executables.
Returns
-------
pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# make the directory that will contain the output files
makedir(output_dir)
# make a node for plotting the acceptance rate
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=output_dir, tags=tags).create_node()
# add command line options
node.add_input_opt("--input-file", mcmc_file)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
# add node to workflow
workflow += node
return node.output_files
def make_inj_info(workflow, injection_file, injection_index, num, out_dir, tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = "page_injinfo"
files = FileList([])
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos, out_dir=out_dir, tags=tags).create_node()
node.add_input_opt("--injection-file", injection_file)
node.add_opt("--injection-index", str(injection_index))
node.add_opt("--n-nearest", str(num))
node.new_output_file_opt(workflow.analysis_time, ".html", "--output-file")
workflow += node
files += node.output_files
return files
def make_inference_samples_plot(
workflow, inference_file, output_dir, parameters=None,
name="inference_samples", analysis_seg=None, tags=None):
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# make the directory that will contain the output files
makedir(output_dir)
# make a node for plotting the posterior as a corner plot
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=output_dir, universe="local",
tags=tags).create_node()
# add command line options
node.add_input_opt("--input-file", inference_file)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
node.add_opt("--parameters", " ".join(parameters))
# add node to workflow
workflow += node
return node.output_files
def make_inference_corner_plot(workflow, inference_file, output_dir,
variable_args=None,
name="inference_posterior", analysis_seg=None, tags=None):
""" Sets up the corner plot of the posteriors in the workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
inference_file: pycbc.workflow.File
The file with posterior samples.
output_dir: str
The directory to store result plots and files.
config_file: str
The path to the inference configuration file that has a
[variable_args] section.
variable_args : list
A list of parameters to use instead of [variable_args].
name: str
The name in the [executables] section of the configuration file
to use.
analysis_segs: {None, glue.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the minifollowups executables.
Returns
-------
pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# make the directory that will contain the output files
makedir(output_dir)
# make a node for plotting the posterior as a corner plot
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=output_dir, universe="local",
tags=tags).create_node()
# add command line options
node.add_input_opt("--input-file", inference_file)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
node.add_opt("--variable-args", " ".join(variable_args))
# add node to workflow
workflow += node
return node.output_files
def make_trigger_timeseries(workflow, singles, coinc, num, out_dir,
exclude=None, require=None, tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'plot_trigger_timeseries'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=out_dir, tags=[tag] + tags).create_node()
node.add_input_list_opt('--single-trigger-files', singles)
node.add_input_opt('--statmap-file', coinc)
node.add_opt('--n-loudest', str(num))
node.new_output_file_opt(workflow.analysis_time, '.png', '--output-file')
workflow += node
files += node.output_files
return files
def make_inference_prior_plot(workflow, config_file, output_dir,
sections=None, name="inference_prior",
analysis_seg=None, tags=None):
""" Sets up the corner plot of the priors in the workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
config_file: pycbc.workflow.File
The WorkflowConfigParser parasable inference configuration file..
output_dir: str
The directory to store result plots and files.
sections : list
A list of subsections to use.
name: str
The name in the [executables] section of the configuration file
to use.
analysis_segs: {None, ligo.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the inference executables.
Returns
-------
pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# make the directory that will contain the output files
makedir(output_dir)
# make a node for plotting the posterior as a corner plot
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=output_dir, universe="local",
tags=tags).create_node()
# add command line options
node.add_input_opt("--config-file", config_file)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
if sections is not None:
node.add_opt("--sections", " ".join(sections))
# add node to workflow
workflow += node
return node.output_files
def make_singles_timefreq(workflow,
single,
bank_file,
trig_time,
out_dir,
veto_file=None,
time_window=10,
data_segments=None,
tags=None):
""" Generate a singles_timefreq node and add it to workflow.
This function generates a single node of the singles_timefreq executable
and adds it to the current workflow. Parent/child relationships are set by
the input/output files automatically.
Parameters
-----------
workflow: pycbc.workflow.core.Workflow
The workflow class that stores the jobs that will be run.
single: pycbc.workflow.core.File instance
The File object storing the single-detector triggers to followup.
bank_file: pycbc.workflow.core.File instance
The File object storing the template bank.
trig_time: int
The time of the trigger being followed up.
out_dir: str
Location of directory to output to
veto_file: File (optional, default=None)
If given use this file to veto triggers to determine the loudest event.
FIXME: Veto files *should* be provided a definer argument and not just
assume that all segments should be read.
time_window: int (optional, default=None)
The amount of data (not including padding) that will be read in by the
singles_timefreq job. The default value of 10s should be fine for most
cases.
data_segments: glue.segments.segmentlist (optional, default=None)
The list of segments for which data exists and can be read in. If given
the start/end times given to singles_timefreq will be adjusted if
[trig_time - time_window, trig_time + time_window] does not completely
lie within a valid data segment. A ValueError will be raised if the
trig_time is not within a valid segment, or if it is not possible to
find 2*time_window (plus the padding) of continuous data around the
trigger. This **must** be coalesced.
tags: list (optional, default=None)
List of tags to add to the created nodes, which determine file naming.
"""
tags = [] if tags is None else tags
makedir(out_dir)
name = 'plot_singles_timefreq'
curr_exe = PlotExecutable(workflow.cp,
name,
ifos=[single.ifo],
out_dir=out_dir,
tags=tags)
node = curr_exe.create_node()
node.add_input_opt('--trig-file', single)
node.add_input_opt('--bank-file', bank_file)
# Determine start/end times, using data segments if needed.
# Begin by choosing "optimal" times
start = trig_time - time_window
end = trig_time + time_window
# Then if data_segments is available, check against that, and move if
# needed
if data_segments is not None:
# Assumes coalesced, so trig_time can only be within one segment
for seg in data_segments:
if trig_time in seg:
data_seg = seg
break
else:
err_msg = "Trig time {} ".format(trig_time)
err_msg += "does not seem to lie within any data segments. "
err_msg += "This shouldn't be possible, please ask for help!"
raise ValueError(err_msg)
# Check for pad-data
if curr_exe.has_opt('pad-data'):
pad_data = int(curr_exe.get_opt('pad-data'))
else:
pad_data = 0
if abs(data_seg) < (2 * time_window + 2 * pad_data):
tl = 2 * time_window + 2 * pad_data
err_msg = "I was asked to use {} seconds of data ".format(tl)
err_msg += "to run a plot_singles_timefreq job. However, I have "
err_msg += "only {} seconds available.".format(abs(data_seg))
raise ValueError(err_msg)
if data_seg[0] > (start - pad_data):
start = data_seg[0] + pad_data
end = start + 2 * time_window
if data_seg[1] < (end + pad_data):
end = data_seg[1] - pad_data
start = end - 2 * time_window
# Sanity check, shouldn't get here!
if data_seg[0] > (start - pad_data):
err_msg = "I shouldn't be here! Go ask Ian what he broke."
raise ValueError(err_msg)
node.add_opt('--gps-start-time', int(start))
node.add_opt('--gps-end-time', int(end))
node.add_opt('--center-time', int(trig_time))
if veto_file:
node.add_input_opt('--veto-file', veto_file)
node.add_opt('--detector', single.ifo)
node.new_output_file_opt(workflow.analysis_time, '.png', '--output-file')
workflow += node
return node.output_files
def make_plot_waveform_plot(workflow, params, out_dir, ifos, exclude=None,
require=None, tags=None):
""" Add plot_waveform jobs to the workflow.
"""
tags = [] if tags is None else tags
makedir(out_dir)
name = 'single_template_plot'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
node = PlotExecutable(workflow.cp, 'plot_waveform', ifos=ifos,
out_dir=out_dir, tags=[tag] + tags).create_node()
node.add_opt('--mass1', "%.6f" % params['mass1'])
node.add_opt('--mass2', "%.6f" % params['mass2'])
node.add_opt('--spin1z',"%.6f" % params['spin1z'])
node.add_opt('--spin2z',"%.6f" % params['spin2z'])
if params.has_key('u_vals'):
# Precessing options
node.add_opt('--spin1x',"%.6f" % params['spin1x'])
node.add_opt('--spin2x',"%.6f" % params['spin2x'])
node.add_opt('--spin1y',"%.6f" % params['spin1y'])
node.add_opt('--spin2y',"%.6f" % params['spin2y'])
node.add_opt('--inclination',"%.6f" % params['inclination'])
node.add_opt('--u-val', "%.6f" % params['u_vals'])
node.new_output_file_opt(workflow.analysis_time, '.png',
'--output-file')
workflow += node
files += node.output_files
return files
def make_singles_timefreq(workflow,
single,
bank_file,
start,
end,
out_dir,
veto_file=None,
tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'plot_singles_timefreq'
node = PlotExecutable(workflow.cp,
name,
ifos=[single.ifo],
out_dir=out_dir,
tags=tags).create_node()
node.add_input_opt('--trig-file', single)
node.add_input_opt('--bank-file', bank_file)
node.add_opt('--gps-start-time', int(start))
node.add_opt('--gps-end-time', int(end))
if veto_file:
node.add_input_opt('--veto-file', veto_file)
node.add_opt('--detector', single.ifo)
node.new_output_file_opt(workflow.analysis_time, '.png', '--output-file')
workflow += node
return node.output_files
def make_coinc_info(workflow, singles, bank, coinc, out_dir,
n_loudest=None, trig_id=None, file_substring=None,
tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'page_coincinfo'
files = FileList([])
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=out_dir, tags=tags).create_node()
node.add_input_list_opt('--single-trigger-files', singles)
node.add_input_opt('--statmap-file', coinc)
node.add_input_opt('--bank-file', bank)
if n_loudest is not None:
node.add_opt('--n-loudest', str(n_loudest))
if trig_id is not None:
node.add_opt('--trigger-id', str(trig_id))
if file_substring is not None:
node.add_opt('--statmap-file-subspace-name', file_substring)
node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
workflow += node
files += node.output_files
return files
def make_inference_plot(workflow,
input_file,
output_dir,
name,
analysis_seg=None,
tags=None,
input_file_opt='input-file',
output_file_extension='.png',
add_to_workflow=False):
"""Boiler-plate function for creating a standard plotting job.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
input_file: (list of) pycbc.workflow.File
The file used for the input. May provide either a single file or a
list of files.
output_dir: str
The directory to store result plots.
name: str
The name in the [executables] section of the configuration file
to use.
analysis_segs: ligo.segments.Segment, optional
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: list, optional
Tags to add to the inference executables.
input_file_opt : str, optional
The name of the input-file option used by the executable. Default
is ``input-file``.
output_file_extension : str, optional
What file type to create. Default is ``.png``.
add_to_workflow : bool, optional
If True, the node will be added to the workflow before being returned.
**This means that no options may be added to the node afterward.**
Default is ``False``.
Returns
-------
pycbc.workflow.plotting.PlotExecutable
The job node for creating the plot.
"""
# default values
if tags is None:
tags = []
if analysis_seg is None:
analysis_seg = workflow.analysis_time
# make the directory that will contain the output files
makedir(output_dir)
# Catch if a parameters option was specified:
# we need to do this because PlotExecutable will automatically add any
# option in the section to the node. However, we need to add the
# appropriate escapes to the parameters option so pegasus will render it
# properly (see _params_for_pegasus for details).
parameters = None
if workflow.cp.has_option(name, 'parameters'):
parameters = workflow.cp.get(name, 'parameters')
workflow.cp.remove_option(name, 'parameters')
# make a node for plotting the posterior as a corner plot
node = PlotExecutable(workflow.cp,
name,
ifos=workflow.ifos,
out_dir=output_dir,
tags=tags).create_node()
# add back the parameters option if it was specified
if parameters is not None:
node.add_opt("--parameters", _params_for_pegasus(parameters))
# and put the opt back in the config file in memory
workflow.cp.set(name, 'parameters', parameters)
# add input and output options
if isinstance(input_file, list):
# list of input files are given, use input_list_opt
node.add_input_list_opt("--{}".format(input_file_opt), input_file)
else:
# assume just a single file
node.add_input_opt("--{}".format(input_file_opt), input_file)
node.new_output_file_opt(analysis_seg, output_file_extension,
"--output-file")
# add node to workflow
if add_to_workflow:
workflow += node
return node
def make_coinc_info(workflow, singles, bank, coinc, num, out_dir, tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'page_coincinfo'
files = FileList([])
node = PlotExecutable(workflow.cp,
name,
ifos=workflow.ifos,
out_dir=out_dir,
tags=tags).create_node()
node.add_input_list_opt('--single-trigger-files', singles)
node.add_input_opt('--statmap-file', coinc)
node.add_input_opt('--bank-file', bank)
node.add_opt('--n-loudest', str(num))
node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
workflow += node
files += node.output_files
return files
def make_singles_timefreq(workflow, single, bank_file, start, end, out_dir,
veto_file=None, tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'plot_singles_timefreq'
node = PlotExecutable(workflow.cp, name, ifos=[single.ifo],
out_dir=out_dir, tags=tags).create_node()
node.add_input_opt('--trig-file', single)
node.add_input_opt('--bank-file', bank_file)
node.add_opt('--gps-start-time', int(start))
node.add_opt('--gps-end-time', int(end))
if veto_file:
node.add_input_opt('--veto-file', veto_file)
node.add_opt('--detector', single.ifo)
node.new_output_file_opt(workflow.analysis_time, '.png', '--output-file')
workflow += node
return node.output_files
def make_inference_single_parameter_plots(workflow,
inference_file,
output_dir,
variable_args=None,
samples_name="inference_samples",
acf_name="inference_acf",
acl_name="inference_acl",
analysis_seg=None,
tags=None):
""" Sets up single-parameter plots for inference workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
inference_file: pycbc.workflow.File
The file with posterior samples.
output_dir: str
The directory to store result plots and files.
variable_args : list
A list of parameters to use instead of [variable_args].
samples_name: str
The name in the [executables] section of the configuration file
to use for the plot that shows all samples.
acf_name: str
The name in the [executables] section of the configuration file
to use for the autocorrelation function plot.
acl_name: str
The name in the [executables] section of the configuration file
to use for the autocorrelation length histogram.
analysis_segs: {None, glue.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the inference executables.
Returns
-------
files: pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# make the directory that will contain the output files
makedir(output_dir)
# list of all output files
files = FileList()
# make a set of plots for each parameter
for arg in variable_args:
# plot posterior distribution
corner_files = make_inference_posterior_plot(workflow,
inference_file,
output_dir,
variable_args=[arg],
analysis_seg=analysis_seg,
tags=tags + [arg])
# make a node for plotting all the samples for each walker
samples_node = PlotExecutable(workflow.cp,
samples_name,
ifos=workflow.ifos,
out_dir=output_dir,
tags=tags + [arg]).create_node()
samples_node.add_input_opt("--input-file", inference_file)
samples_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
samples_node.add_opt("--parameters", arg)
# make node for plotting the autocorrelation function for each walker
acf_node = PlotExecutable(workflow.cp,
acf_name,
ifos=workflow.ifos,
out_dir=output_dir,
tags=tags + [arg]).create_node()
acf_node.add_input_opt("--input-file", inference_file)
acf_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
acf_node.add_opt("--parameters", arg)
# make node for plotting the autocorrelation function for each walker
acl_node = PlotExecutable(workflow.cp,
acl_name,
ifos=workflow.ifos,
out_dir=output_dir,
tags=tags + [arg]).create_node()
acl_node.add_input_opt("--input-file", inference_file)
acl_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
acl_node.add_opt("--parameters", arg)
# add nodes to workflow
workflow += samples_node
workflow += acf_node
workflow += acl_node
# add files to output files list
files += corner_files
files += samples_node.output_files
files += acf_node.output_files
files += acl_node.output_files
return files
def make_plot_waveform_plot(workflow, params, out_dir, ifos, exclude=None, require=None, tags=None):
""" Add plot_waveform jobs to the workflow.
"""
tags = [] if tags is None else tags
makedir(out_dir)
name = "single_template_plot"
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
node = PlotExecutable(workflow.cp, "plot_waveform", ifos=ifos, out_dir=out_dir, tags=[tag] + tags).create_node()
node.add_opt("--mass1", "%.6f" % params["mass1"])
node.add_opt("--mass2", "%.6f" % params["mass2"])
node.add_opt("--spin1z", "%.6f" % params["spin1z"])
node.add_opt("--spin2z", "%.6f" % params["spin2z"])
if params.has_key("u_vals"):
# Precessing options
node.add_opt("--spin1x", "%.6f" % params["spin1x"])
node.add_opt("--spin2x", "%.6f" % params["spin2x"])
node.add_opt("--spin1y", "%.6f" % params["spin1y"])
node.add_opt("--spin2y", "%.6f" % params["spin2y"])
node.add_opt("--inclination", "%.6f" % params["inclination"])
node.add_opt("--u-val", "%.6f" % params["u_vals"])
node.new_output_file_opt(workflow.analysis_time, ".png", "--output-file")
workflow += node
files += node.output_files
return files
def make_single_template_plots(workflow,
segs,
seg_name,
coinc,
bank,
num,
out_dir,
exclude=None,
require=None,
tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'single_template_plot'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
for ifo in workflow.ifos:
# Reanalyze the time around the trigger in each detector
node = PlotExecutable(workflow.cp,
'single_template',
ifos=[ifo],
out_dir=out_dir,
tags=[tag] + tags).create_node()
node.add_input_opt('--statmap-file', coinc)
node.add_opt('--n-loudest', str(num))
node.add_input_opt('--inspiral-segments', segs[ifo])
node.add_opt('--segment-name', seg_name)
node.add_input_opt('--bank-file', bank)
node.new_output_file_opt(workflow.analysis_time, '.hdf',
'--output-file')
data = node.output_files[0]
workflow += node
# Make the plot for this trigger and detector
node = PlotExecutable(workflow.cp,
name,
ifos=[ifo],
out_dir=out_dir,
tags=[tag] + tags).create_node()
node.add_input_opt('--single-template-file', data)
node.new_output_file_opt(workflow.analysis_time, '.png',
'--output-file')
workflow += node
files += node.output_files
return files
def make_sngl_ifo(workflow, sngl_file, bank_file, trigger_id, out_dir, ifo, tags=None, rank=None):
"""Setup a job to create sngl detector sngl ifo html summary snippet.
"""
tags = [] if tags is None else tags
makedir(out_dir)
name = "page_snglinfo"
files = FileList([])
node = PlotExecutable(workflow.cp, name, ifos=[ifo], out_dir=out_dir, tags=tags).create_node()
node.add_input_opt("--single-trigger-file", sngl_file)
node.add_input_opt("--bank-file", bank_file)
node.add_opt("--trigger-id", str(trigger_id))
if rank is not None:
node.add_opt("--n-loudest", str(rank))
node.add_opt("--instrument", ifo)
node.new_output_file_opt(workflow.analysis_time, ".html", "--output-file")
workflow += node
files += node.output_files
return files
def make_coinc_info(workflow, singles, bank, coinc, out_dir,
n_loudest=None, trig_id=None, file_substring=None,
sort_order=None, sort_var=None, tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'page_coincinfo'
files = FileList([])
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=out_dir, tags=tags).create_node()
node.add_input_list_opt('--single-trigger-files', singles)
node.add_input_opt('--statmap-file', coinc)
node.add_input_opt('--bank-file', bank)
if sort_order:
node.add_opt('--sort-order', sort_order)
if sort_var:
node.add_opt('--sort-variable', sort_var)
if n_loudest is not None:
node.add_opt('--n-loudest', str(n_loudest))
if trig_id is not None:
node.add_opt('--trigger-id', str(trig_id))
if file_substring is not None:
node.add_opt('--statmap-file-subspace-name', file_substring)
node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
workflow += node
files += node.output_files
return files
def make_inference_single_parameter_plots(workflow, mcmc_file, output_dir,
config_file, samples_name="mcmc_samples",
auto_name="mcmc_acf", analysis_seg=None, tags=None):
""" Sets up single-parameter plots from MCMC in the workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
mcmc_file: pycbc.workflow.File
The file with MCMC samples.
output_dir: str
The directory to store result plots and files.
config_file: str
The path to the inference configuration file that has a
[variable_args] section.
samples_name: str
The name in the [executables] section of the configuration file
to use for the plot that shows all samples.
auto_name: str
The name in the [executables] section of the configuration file
to use for the autocorrelation function plot.
analysis_segs: {None, glue.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the minifollowups executables.
Returns
-------
files: pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# read config file to get variables that vary
cp = WorkflowConfigParser([config_file])
variable_args = cp.options("variable_args")
# make the directory that will contain the output files
makedir(output_dir)
# list of all output files
files = FileList()
# make a set of plots for each parameter
for arg in variable_args:
# make a node for plotting all the samples
samples_node = PlotExecutable(workflow.cp, samples_name,
ifos=workflow.ifos, out_dir=output_dir,
tags=tags + [arg]).create_node()
# add command line options
samples_node.add_input_opt("--input-file", mcmc_file)
samples_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
samples_node.add_opt("--variable-args", arg)
samples_node.add_opt("--labels", arg)
# make node for plotting the autocorrelation function for each walker
auto_node = PlotExecutable(workflow.cp, auto_name, ifos=workflow.ifos,
out_dir=output_dir, tags=tags + [arg]).create_node()
# add command line options
auto_node.add_input_opt("--input-file", mcmc_file)
auto_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
auto_node.add_opt("--variable-args", arg)
# add nodes to workflow
workflow += samples_node
workflow += auto_node
# add files to output files list
files += samples_node.output_files
files += auto_node.output_files
return files
def make_coinc_info(workflow, singles, bank, coinc, num, out_dir, tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'page_coincinfo'
files = FileList([])
node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=out_dir, tags=tags).create_node()
node.add_input_list_opt('--single-trigger-files', singles)
node.add_input_opt('--statmap-file', coinc)
node.add_input_opt('--bank-file', bank)
node.add_opt('--n-loudest', str(num))
node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
workflow += node
files += node.output_files
return files
def make_plot_waveform_plot(workflow, params, out_dir, ifos, exclude=None,
require=None, tags=None):
""" Add plot_waveform jobs to the workflow.
"""
tags = [] if tags is None else tags
makedir(out_dir)
name = 'single_template_plot'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
node = PlotExecutable(workflow.cp, 'plot_waveform', ifos=ifos,
out_dir=out_dir, tags=[tag] + tags).create_node()
node.add_opt('--mass1', "%.6f" % params['mass1'])
node.add_opt('--mass2', "%.6f" % params['mass2'])
node.add_opt('--spin1z',"%.6f" % params['spin1z'])
node.add_opt('--spin2z',"%.6f" % params['spin2z'])
if 'u_vals' in params:
# Precessing options
node.add_opt('--spin1x',"%.6f" % params['spin1x'])
node.add_opt('--spin2x',"%.6f" % params['spin2x'])
node.add_opt('--spin1y',"%.6f" % params['spin1y'])
node.add_opt('--spin2y',"%.6f" % params['spin2y'])
node.add_opt('--inclination',"%.6f" % params['inclination'])
node.add_opt('--u-val', "%.6f" % params['u_vals'])
node.new_output_file_opt(workflow.analysis_time, '.png',
'--output-file')
workflow += node
files += node.output_files
return files
def make_sngl_ifo(workflow, sngl_file, bank_file, num, out_dir, ifo,
veto_file=None, veto_segment_name=None, tags=None):
"""Setup a job to create sngl detector sngl ifo html summary snippet.
"""
tags = [] if tags is None else tags
makedir(out_dir)
name = 'page_snglinfo'
files = FileList([])
node = PlotExecutable(workflow.cp, name, ifos=[ifo],
out_dir=out_dir, tags=tags).create_node()
node.add_input_opt('--single-trigger-file', sngl_file)
node.add_input_opt('--bank-file', bank_file)
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)
node.add_opt('--n-loudest', str(num))
node.add_opt('--instrument', ifo)
node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
workflow += node
files += node.output_files
return files
def make_inference_single_parameter_plots(workflow, inference_file, output_dir,
variable_args=None, samples_name="inference_samples",
acf_name="inference_acf", acl_name="inference_acl",
analysis_seg=None, tags=None):
""" Sets up single-parameter plots for inference workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
inference_file: pycbc.workflow.File
The file with posterior samples.
output_dir: str
The directory to store result plots and files.
variable_args : list
A list of parameters to use instead of [variable_args].
samples_name: str
The name in the [executables] section of the configuration file
to use for the plot that shows all samples.
acf_name: str
The name in the [executables] section of the configuration file
to use for the autocorrelation function plot.
acl_name: str
The name in the [executables] section of the configuration file
to use for the autocorrelation length histogram.
analysis_segs: {None, glue.segments.Segment}
The segment this job encompasses. If None then use the total analysis
time from the workflow.
tags: {None, optional}
Tags to add to the inference executables.
Returns
-------
files: pycbc.workflow.FileList
A list of result and output files.
"""
# default values
tags = [] if tags is None else tags
analysis_seg = workflow.analysis_time \
if analysis_seg is None else analysis_seg
# make the directory that will contain the output files
makedir(output_dir)
# list of all output files
files = FileList()
# make a set of plots for each parameter
for arg in variable_args:
# plot posterior distribution
corner_files = make_inference_posterior_plot(workflow, inference_file,
output_dir, variable_args=[arg],
analysis_seg=analysis_seg, tags=tags + [arg])
# make a node for plotting all the samples for each walker
samples_node = PlotExecutable(workflow.cp, samples_name,
ifos=workflow.ifos, out_dir=output_dir,
tags=tags + [arg]).create_node()
samples_node.add_input_opt("--input-file", inference_file)
samples_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
samples_node.add_opt("--parameters", arg)
# make node for plotting the autocorrelation function for each walker
acf_node = PlotExecutable(workflow.cp, acf_name, ifos=workflow.ifos,
out_dir=output_dir, tags=tags + [arg]).create_node()
acf_node.add_input_opt("--input-file", inference_file)
acf_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
acf_node.add_opt("--parameters", arg)
# make node for plotting the autocorrelation function for each walker
acl_node = PlotExecutable(workflow.cp, acl_name, ifos=workflow.ifos,
out_dir=output_dir, tags=tags + [arg]).create_node()
acl_node.add_input_opt("--input-file", inference_file)
acl_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
acl_node.add_opt("--parameters", arg)
# add nodes to workflow
workflow += samples_node
workflow += acf_node
workflow += acl_node
# add files to output files list
files += corner_files
files += samples_node.output_files
files += acf_node.output_files
files += acl_node.output_files
return files
def make_single_template_plots(workflow, segs, data_read_name, analyzed_name,
params, out_dir, inj_file=None, exclude=None,
require=None, tags=None, params_str=None,
use_exact_inj_params=False):
"""Function for creating jobs to run the pycbc_single_template code and
to run the associated plotting code pycbc_single_template_plots and add
these jobs to the workflow.
Parameters
-----------
workflow : workflow.Workflow instance
The pycbc.workflow.Workflow instance to add these jobs to.
segs : workflow.File instance
The pycbc.workflow.File instance that points to the XML file containing
the segment lists of data read in and data analyzed.
data_read_name : str
The name of the segmentlist containing the data read in by each
inspiral job in the segs file.
analyzed_name : str
The name of the segmentlist containing the data analyzed by each
inspiral job in the segs file.
params : dictionary
A dictionary containing the parameters of the template to be used.
params[ifo+'end_time'] is required for all ifos in workflow.ifos.
If use_exact_inj_params is False then also need to supply values for
[mass1, mass2, spin1z, spin2x]. For precessing templates one also
needs to supply [spin1y, spin1x, spin2x, spin2y, inclination]
additionally for precession one must supply u_vals or
u_vals_+ifo for all ifos. u_vals is the ratio between h_+ and h_x to
use when constructing h(t). h(t) = (h_+ * u_vals) + h_x.
out_dir : str
Directory in which to store the output files.
inj_file : workflow.File (optional, default=None)
If given send this injection file to the job so that injections are
made into the data.
exclude : list (optional, default=None)
If given, then when considering which subsections in the ini file to
parse for options to add to single_template_plot, only use subsections
that *do not* match strings in this list.
require : list (optional, default=None)
If given, then when considering which subsections in the ini file to
parse for options to add to single_template_plot, only use subsections
matching strings in this list.
tags : list (optional, default=None)
Add this list of tags to all jobs.
params_str : str (optional, default=None)
If given add this string to plot title and caption to describe the
template that was used.
use_exact_inj_params : boolean (optional, default=False)
If True do not use masses and spins listed in the params dictionary
but instead use the injection closest to the filter time as a template.
Returns
--------
output_files : workflow.FileList
The list of workflow.Files created in this function.
"""
tags = [] if tags is None else tags
makedir(out_dir)
name = 'single_template_plot'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
for ifo in workflow.ifos:
if params['%s_end_time' % ifo] == -1.0:
continue
# Reanalyze the time around the trigger in each detector
node = SingleTemplateExecutable(workflow.cp, 'single_template',
ifos=[ifo], out_dir=out_dir,
tags=[tag] + tags).create_node()
if use_exact_inj_params:
node.add_opt('--use-params-of-closest-injection')
else:
node.add_opt('--mass1', "%.6f" % params['mass1'])
node.add_opt('--mass2', "%.6f" % params['mass2'])
node.add_opt('--spin1z',"%.6f" % params['spin1z'])
node.add_opt('--spin2z',"%.6f" % params['spin2z'])
node.add_opt('--template-start-frequency',
"%.6f" % params['f_lower'])
# Is this precessing?
if 'u_vals' in params or 'u_vals_%s' % ifo in params:
node.add_opt('--spin1x',"%.6f" % params['spin1x'])
node.add_opt('--spin1y',"%.6f" % params['spin1y'])
node.add_opt('--spin2x',"%.6f" % params['spin2x'])
node.add_opt('--spin2y',"%.6f" % params['spin2y'])
node.add_opt('--inclination',"%.6f" % params['inclination'])
try:
node.add_opt('--u-val',"%.6f" % params['u_vals'])
except:
node.add_opt('--u-val',
"%.6f" % params['u_vals_%s' % ifo])
# str(numpy.float64) restricts to 2d.p. BE CAREFUL WITH THIS!!!
str_trig_time = '%.6f' %(params[ifo + '_end_time'])
node.add_opt('--trigger-time', str_trig_time)
node.add_input_opt('--inspiral-segments', segs)
if inj_file is not None:
node.add_input_opt('--injection-file', inj_file)
node.add_opt('--data-read-name', data_read_name)
node.add_opt('--data-analyzed-name', analyzed_name)
node.new_output_file_opt(workflow.analysis_time, '.hdf',
'--output-file', store_file=False)
data = node.output_files[0]
workflow += node
# Make the plot for this trigger and detector
node = PlotExecutable(workflow.cp, name, ifos=[ifo],
out_dir=out_dir, tags=[tag] + tags).create_node()
node.add_input_opt('--single-template-file', data)
node.new_output_file_opt(workflow.analysis_time, '.png',
'--output-file')
title="'%s SNR and chi^2 timeseries" %(ifo)
if params_str is not None:
title+= " using %s" %(params_str)
title+="'"
node.add_opt('--plot-title', title)
caption = "'The SNR and chi^2 timeseries around the injection"
if params_str is not None:
caption += " using %s" %(params_str)
if use_exact_inj_params:
caption += ". The injection itself was used as the template.'"
else:
caption += ". The template used has the following parameters: "
caption += "mass1=%s, mass2=%s, spin1z=%s, spin2z=%s'"\
%(params['mass1'], params['mass2'], params['spin1z'],
params['spin2z'])
node.add_opt('--plot-caption', caption)
workflow += node
files += node.output_files
return files
def make_single_template_plots(workflow,
segs,
seg_name,
params,
out_dir,
inj_file=None,
exclude=None,
require=None,
tags=None,
params_str=None,
use_exact_inj_params=False):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'single_template_plot'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
for ifo in workflow.ifos:
# Reanalyze the time around the trigger in each detector
node = PlotExecutable(workflow.cp,
'single_template',
ifos=[ifo],
out_dir=out_dir,
tags=[tag] + tags).create_node()
if use_exact_inj_params:
node.add_opt('--use-params-of-closest-injection')
else:
node.add_opt('--mass1', "%.6f" % params['mass1'])
node.add_opt('--mass2', "%.6f" % params['mass2'])
node.add_opt('--spin1z', "%.6f" % params['spin1z'])
node.add_opt('--spin2z', "%.6f" % params['spin2z'])
# str(numpy.float64) restricts to 2d.p. BE CAREFUL WITH THIS!!!
str_trig_time = '%.6f' % (params[ifo + '_end_time'])
node.add_opt('--trigger-time', str_trig_time)
node.add_input_opt('--inspiral-segments', segs[ifo])
if inj_file is not None:
node.add_input_opt('--injection-file', inj_file)
node.add_opt('--segment-name', seg_name)
node.new_output_file_opt(workflow.analysis_time,
'.hdf',
'--output-file',
store_file=False)
data = node.output_files[0]
workflow += node
# Make the plot for this trigger and detector
node = PlotExecutable(workflow.cp,
name,
ifos=[ifo],
out_dir=out_dir,
tags=[tag] + tags).create_node()
node.add_input_opt('--single-template-file', data)
node.new_output_file_opt(workflow.analysis_time, '.png',
'--output-file')
title = "'%s SNR and chi^2 timeseries" % (ifo)
if params_str is not None:
title += " using %s" % (params_str)
title += "'"
node.add_opt('--plot-title', title)
caption = "'The SNR and chi^2 timeseries around the injection"
if params_str is not None:
caption += " using %s" % (params_str)
if use_exact_inj_params:
caption += ". The injection itself was used as the template.'"
else:
caption += ". The template used has the following parameters: "
caption += "mass1=%s, mass2=%s, spin1z=%s, spin2z=%s'"\
%(params['mass1'], params['mass2'], params['spin1z'],
params['spin2z'])
node.add_opt('--plot-caption', caption)
workflow += node
files += node.output_files
return files
def make_sngl_ifo(workflow,
sngl_file,
bank_file,
num,
out_dir,
ifo,
veto_file=None,
veto_segment_name=None,
tags=None):
"""Setup a job to create sngl detector sngl ifo html summary snippet.
"""
tags = [] if tags is None else tags
makedir(out_dir)
name = 'page_snglinfo'
files = FileList([])
node = PlotExecutable(workflow.cp,
name,
ifos=[ifo],
out_dir=out_dir,
tags=tags).create_node()
node.add_input_opt('--single-trigger-file', sngl_file)
node.add_input_opt('--bank-file', bank_file)
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)
node.add_opt('--n-loudest', str(num))
node.add_opt('--instrument', ifo)
node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
workflow += node
files += node.output_files
return files
def make_single_template_plots(workflow, segs, seg_name, params,
out_dir, inj_file=None, exclude=None,
require=None, tags=None, params_str=None,
use_exact_inj_params=False):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'single_template_plot'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
for ifo in workflow.ifos:
# Reanalyze the time around the trigger in each detector
node = PlotExecutable(workflow.cp, 'single_template', ifos=[ifo],
out_dir=out_dir, tags=[tag] + tags).create_node()
if use_exact_inj_params:
node.add_opt('--use-params-of-closest-injection')
else:
node.add_opt('--mass1', "%.6f" % params['mass1'])
node.add_opt('--mass2', "%.6f" % params['mass2'])
node.add_opt('--spin1z',"%.6f" % params['spin1z'])
node.add_opt('--spin2z',"%.6f" % params['spin2z'])
# str(numpy.float64) restricts to 2d.p. BE CAREFUL WITH THIS!!!
str_trig_time = '%.6f' %(params[ifo + '_end_time'])
node.add_opt('--trigger-time', str_trig_time)
node.add_input_opt('--inspiral-segments', segs)
if inj_file is not None:
node.add_input_opt('--injection-file', inj_file)
node.add_opt('--segment-name', seg_name)
node.new_output_file_opt(workflow.analysis_time, '.hdf',
'--output-file', store_file=False)
data = node.output_files[0]
workflow += node
# Make the plot for this trigger and detector
node = PlotExecutable(workflow.cp, name, ifos=[ifo],
out_dir=out_dir, tags=[tag] + tags).create_node()
node.add_input_opt('--single-template-file', data)
node.new_output_file_opt(workflow.analysis_time, '.png',
'--output-file')
title="'%s SNR and chi^2 timeseries" %(ifo)
if params_str is not None:
title+= " using %s" %(params_str)
title+="'"
node.add_opt('--plot-title', title)
caption = "'The SNR and chi^2 timeseries around the injection"
if params_str is not None:
caption += " using %s" %(params_str)
if use_exact_inj_params:
caption += ". The injection itself was used as the template.'"
else:
caption += ". The template used has the following parameters: "
caption += "mass1=%s, mass2=%s, spin1z=%s, spin2z=%s'"\
%(params['mass1'], params['mass2'], params['spin1z'],
params['spin2z'])
node.add_opt('--plot-caption', caption)
workflow += node
files += node.output_files
return files
def make_sngl_ifo(workflow, sngl_file, bank_file, trigger_id, out_dir, ifo,
tags=None):
"""Setup a job to create sngl detector sngl ifo html summary snippet.
"""
tags = [] if tags is None else tags
makedir(out_dir)
name = 'page_snglinfo'
files = FileList([])
node = PlotExecutable(workflow.cp, name, ifos=[ifo],
out_dir=out_dir, tags=tags).create_node()
node.add_input_opt('--single-trigger-file', sngl_file)
node.add_input_opt('--bank-file', bank_file)
node.add_opt('--trigger-id', str(trigger_id))
node.add_opt('--instrument', ifo)
node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
workflow += node
files += node.output_files
return files
def make_single_template_plots(workflow, segs, seg_name, coinc, bank, num, out_dir,
exclude=None, require=None, tags=None):
tags = [] if tags is None else tags
makedir(out_dir)
name = 'single_template_plot'
secs = requirestr(workflow.cp.get_subsections(name), require)
secs = excludestr(secs, exclude)
files = FileList([])
for tag in secs:
for ifo in workflow.ifos:
# Reanalyze the time around the trigger in each detector
node = PlotExecutable(workflow.cp, 'single_template', ifos=[ifo],
out_dir=out_dir, tags=[tag] + tags).create_node()
node.add_input_opt('--statmap-file', coinc)
node.add_opt('--n-loudest', str(num))
node.add_input_opt('--inspiral-segments', segs[ifo])
node.add_opt('--segment-name', seg_name)
node.add_input_opt('--bank-file', bank)
node.new_output_file_opt(workflow.analysis_time, '.hdf', '--output-file')
data = node.output_files[0]
workflow += node
# Make the plot for this trigger and detector
node = PlotExecutable(workflow.cp, name, ifos=[ifo],
out_dir=out_dir, tags=[tag] + tags).create_node()
node.add_input_opt('--single-template-file', data)
node.new_output_file_opt(workflow.analysis_time, '.png', '--output-file')
workflow += node
files += node.output_files
return files
