def cut_distant_injections(workflow, inj_file, out_dir, tags=None):
    "Set up a job for removing injections that are too distant to be seen"
    if tags is None:
        tags = []

    node = Executable(workflow.cp, 'inj_cut', ifos=workflow.ifos,
                      out_dir=out_dir, tags=tags).create_node()
    node.add_input_opt('--input', inj_file)
    node.new_output_file_opt(workflow.analysis_time, '.xml', '--output-file')
    workflow += node
    return node.output_files[0]

def compute_inj_optimal_snr(workflow, inj_file, precalc_psd_files, out_dir,
                            tags=None):
    "Set up a job for computing optimal SNRs of a sim_inspiral file."
    if tags is None:
        tags = []

    node = Executable(workflow.cp, 'optimal_snr', ifos=workflow.ifos,
                      out_dir=out_dir, tags=tags).create_node()
    node.add_input_opt('--input-file', inj_file)
    node.add_input_list_opt('--time-varying-psds', precalc_psd_files)
    node.new_output_file_opt(workflow.analysis_time, '.xml', '--output-file')
    workflow += node
    return node.output_files[0]

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 = wdax.File(os.path.basename(config_path))
    config_file.PFN(config_path, 'local')
    
    exe = Executable(workflow.cp, 'foreground_minifollowup', ifos=workflow.ifos, out_dir=dax_output)
    
    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)
    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)

    name = node.output_files[0].name
    map_loc = node.output_files[1].name

    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 = dax.DAX(fil)
    job.addArguments('--basename %s' % os.path.splitext(os.path.basename(name))[0])
    Workflow.set_job_properties(job, map_loc)
    workflow._adag.addJob(job)
    dep = dax.Dependency(parent=node._dax_node, child=job)
    workflow._adag.addDependency(dep)
    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, 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
    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 = wdax.File(os.path.basename(config_path))
    config_file.PFN(config_path, 'local')

    exe = Executable(workflow.cp, 'singles_minifollowup',
                     ifos=curr_ifo, out_dir=dax_output, tags=tags)

    wikifile = curr_ifo + '_'.join(tags) + 'loudest_table.txt'

    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)
    node.add_opt('--wiki-file', wikifile)
    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.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)

    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 = 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)
    dep = dax.Dependency(parent=node._dax_node, child=job)
    workflow._adag.addDependency(dep)
    logging.info('Leaving minifollowups module')

def create_segs_from_cats_job(cp, out_dir, ifo_string, tag=None):
    """
    This function creates the CondorDAGJob that will be used to run 
    ligolw_segments_from_cats as part of the workflow

    Parameters
    -----------
    cp : pycbc.workflow.configuration.WorkflowConfigParser
        The in-memory representation of the configuration (.ini) files
    out_dir : path
        Directory in which to put output files
    ifo_string : string
        String containing all active ifos, ie. "H1L1V1"
    tag : string, optional (default=None)
        Use this to specify a tag. This can be used if this module is being
        called more than once to give call specific configuration (by setting
        options in [workflow-datafind-${TAG}] rather than [workflow-datafind]). This
        is also used to tag the Files returned by the class to uniqueify
        the Files and uniqueify the actual filename.
        FIXME: Filenames may not be unique with current codes!

    Returns
    --------
    job : Job instance
        The Job instance that will run segments_from_cats jobs
    """
    segServerUrl = cp.get_opt_tags("workflow-segments", 
                                   "segments-database-url", [tag])
    vetoDefFile = cp.get_opt_tags("workflow-segments", 
                                  "segments-veto-definer-file", [tag])

    if tag:
        currTags = [tag]
    else:
        currTags = []
    job = Executable(cp, 'segments_from_cats', universe='local',
                               ifos=ifo_string, out_dir=out_dir, tags=currTags)
    job.add_opt('--separate-categories')
    job.add_opt('--segment-url', segServerUrl)
    
    job.add_opt('--veto-file', vetoDefFile)
    # FIXME: Would like the proxy in the Workflow instance
    # FIXME: Explore using the x509 condor commands
    # Set up proxy to be accessible in a NFS location
    # If the user has logged in with gsissh then X509_USER_PROXY will be set
    # However, certain users log in with an ssh key and then ligo-proxy-init
    # This route does not set X509_USER_PROXY, so use the default file location
    if os.environ.has_key('X509_USER_PROXY'):
        proxy = os.getenv('X509_USER_PROXY')
    else:
        proxy = "/tmp/x509up_u%d" % os.getuid()
    proxyfile = os.path.join(out_dir, 'x509up.file')
    try:
        shutil.copyfile(proxy, proxyfile)
    except IOError:
        raise RuntimeError('Cannot find certificate in %s. '
                           'Make sure that ligo-proxy-init ' 
                           'has been run.' % proxy)
                           
        
    job.add_profile('condor', 'environment',
                       'USER=$ENV(USER);X509_USER_PROXY=%s' % proxyfile)

    return job

 def create_node(self):
     node = Executable.create_node(self)
     node.set_priority(1000)
     return node

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 minifollowups result plots and files
    tags: {None, optional}
        Tags to add to the minifollowups 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_inference.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_loc = node.output_files[1].name
    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_loc)
    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")

def setup_injection_minifollowups(
    workflow,
    injection_file,
    inj_xml_file,
    single_triggers,
    tmpltbank_file,
    insp_segs,
    insp_data_name,
    insp_anal_name,
    dax_output,
    out_dir,
    tags=None,
):
    """ Create plots that followup the closest missed injections
    
    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 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 injection minifollowups module")

    if not workflow.cp.has_section("workflow-injection_minifollowups"):
        logging.info("There is no [workflow-injection_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) + "injection_minifollowup.ini")
    workflow.cp.write(open(config_path, "w"))

    config_file = wdax.File(os.path.basename(config_path))
    config_file.PFN(config_path, "local")

    exe = Executable(workflow.cp, "injection_minifollowup", ifos=workflow.ifos, out_dir=dax_output)

    node = exe.create_node()
    node.add_input_opt("--config-files", config_file)
    node.add_input_opt("--bank-file", tmpltbank_file)
    node.add_input_opt("--injection-file", injection_file)
    node.add_input_opt("--injection-xml-file", inj_xml_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)
    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)

    name = node.output_files[0].name
    map_loc = node.output_files[1].name

    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 = dax.DAX(fil)
    job.addArguments("--basename %s" % os.path.splitext(os.path.basename(name))[0])
    Workflow.set_job_properties(job, map_loc)
    workflow._adag.addJob(job)
    dep = dax.Dependency(parent=node._dax_node, child=job)
    workflow._adag.addDependency(dep)
    logging.info("Leaving injection minifollowups module")

def veto_injections(workflow, inj_file, veto_file, veto_name, out_dir, tags=None):
    tags = [] if tags is None else tags
    make_analysis_dir(out_dir)
    
    node = Executable(workflow.cp, 'strip_injections', ifos=workflow.ifos,
                          out_dir=out_dir, tags=tags).create_node()
    node.add_opt('--segment-name', veto_name)
    node.add_input_opt('--veto-file', veto_file)
    node.add_input_opt('--injection-file', inj_file)
    node.add_opt('--ifos', ' '.join(workflow.ifos))
    node.new_output_file_opt(workflow.analysis_time, '.xml', '--output-file')
    workflow += node
    return node.output_files[0]