# Copyright (C) 2016 Christopher M. Biwer, Alexander Harvey Nitz
#
# 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.
"""
Module that contains functions for setting up the inference workflow.
"""
import logging
import os.path
from Pegasus import DAX3 as dax
from pycbc.workflow.core import (Executable, FileList, makedir, Workflow)
from pycbc.workflow.plotting import PlotExecutable
from pycbc.workflow import pegasus_workflow as wdax
[docs]def setup_foreground_inference(workflow, coinc_file, single_triggers,
tmpltbank_file, insp_segs, insp_data_name,
insp_anal_name, dax_output, out_dir, tags=None):
""" Creates workflow node that will run the inference workflow.
Parameters
----------
workflow: pycbc.workflow.Workflow
The core workflow instance we are populating
coinc_file: pycbc.workflow.File
The file associated with coincident triggers.
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.
dax_output : str
The name of the output DAX file.
out_dir: path
The directory to store inference result plots and files
tags: {None, optional}
Tags to add to the inference executables
"""
logging.info("Entering inference module")
# check if configuration file has inference section
if not workflow.cp.has_section("workflow-inference"):
logging.info("There is no [workflow-inference] section in "
"configuration file")
logging.info("Leaving inference module")
return
# default tags is a list
tags = [] if tags is None else tags
# make the directory that will contain the dax file
makedir(dax_output)
# turn the config file into a File class
config_path = os.path.abspath(dax_output + "/" + "_".join(tags) +
"foreground_gwin.ini")
workflow.cp.write(open(config_path, "w"))
config_file = wdax.File(os.path.basename(config_path))
config_file.PFN(config_path, "local")
# create an Executable for the inference workflow generator
exe = Executable(workflow.cp, "foreground_inference", ifos=workflow.ifos,
out_dir=dax_output)
# create the node that will run in the workflow
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.new_output_file_opt(workflow.analysis_time, ".dax", "--output-file",
tags=tags)
node.new_output_file_opt(workflow.analysis_time, ".dax.map",
"--output-map", tags=tags)
# get dax name and use it for the workflow name
name = node.output_files[0].name
node.add_opt("--workflow-name", name)
# get output map name and use it for the output dir name
map_file = node.output_files[1]
node.add_opt("--output-dir", out_dir)
# add this node to the workflow
workflow += node
# create job for dax that will run a sub-workflow
# and add it to the workflow
fil = node.output_files[0]
job = dax.DAX(fil)
job.addArguments(
"--basename %s" % os.path.splitext(os.path.basename(name))[0])
Workflow.set_job_properties(job, map_file)
workflow._adag.addJob(job)
# make dax a child of the inference workflow generator node
dep = dax.Dependency(parent=node._dax_node, child=job)
workflow._adag.addDependency(dep)
logging.info("Leaving inference module")
[docs]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, 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
-------
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
[docs]def make_inference_summary_table(workflow, inference_file, output_dir,
variable_params=None, name="inference_table",
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.
variable_params : list
A list of parameters to use instead of [variable_params].
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 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, tags=tags).create_node()
# add command line options
node.add_input_opt("--input-file", inference_file)
node.new_output_file_opt(analysis_seg, ".html", "--output-file")
node.add_opt("--parameters", " ".join(variable_params))
# add node to workflow
workflow += node
return node.output_files
[docs]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, 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
-------
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
[docs]def make_inference_1d_posterior_plots(
workflow, inference_file, output_dir, parameters=None,
analysis_seg=None, tags=None):
parameters = [] if parameters is None else parameters
files = FileList([])
for parameter in parameters:
files += make_inference_posterior_plot(
workflow, inference_file, output_dir,
parameters=[parameter], analysis_seg=analysis_seg,
tags=tags + [parameter])
return files
[docs]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
[docs]def make_inference_acceptance_rate_plot(workflow, inference_file, output_dir,
name="inference_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
inference_file: pycbc.workflow.File
The file with posterior 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 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 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", inference_file)
node.new_output_file_opt(analysis_seg, ".png", "--output-file")
# add node to workflow
workflow += node
return node.output_files
[docs]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, 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
-------
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 param in parameters:
plot_exe = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
out_dir=output_dir, tags=tags + [param])
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