# Copyright (C) 2015 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. import logging, os.path from ligo import segments from pycbc.workflow.core import Executable, FileList from pycbc.workflow.core import makedir, resolve_url_to_file from pycbc.workflow.plotting import PlotExecutable, requirestr, excludestr try: # Python 3 from itertools import zip_longest except ImportError: # Python 2 from itertools import izip_longest as zip_longest from pycbc.workflow.pegasus_workflow import SubWorkflow def grouper(iterable, n, fillvalue=None): """ Create a list of n length tuples """ args = [iter(iterable)] * n return zip_longest(*args, fillvalue=fillvalue) 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) node.add_opt('--dax-file-directory', '.') 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) 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) node.add_opt('--dax-file-directory', '.') 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) logging.info('Leaving minifollowups 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 = resolve_url_to_file(config_path) 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) if tags: node.add_list_opt('--tags', tags) node.new_output_file_opt(workflow.analysis_time, '.dax', '--dax-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) node.add_opt('--dax-file-directory', '.') workflow += node # execute this in a sub-workflow fil = node.output_files[0] job = SubWorkflow(fil.name, is_planned=False) input_files = [tmpltbank_file, injection_file, inj_xml_file, insp_segs] input_files += 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) logging.info('Leaving injection minifollowups module') class SingleTemplateExecutable(PlotExecutable): """Class to be used for to create workflow.Executable instances for the pycbc_single_template executable. Basically inherits directly from PlotExecutable. """ time_dependent_options = ['--channel-name', '--frame-type'] class SingleTimeFreqExecutable(PlotExecutable): """Class to be used for to create workflow.Executable instances for the pycbc_plot_singles_timefreq executable. Basically inherits directly from PlotExecutable. """ time_dependent_options = ['--channel-name', '--frame-type'] class PlotQScanExecutable(PlotExecutable): """Class to be used for to create workflow.Executable instances for the pycbc_plot_qscan executable. Basically inherits directly from PlotExecutable. """ time_dependent_options = ['--channel-name', '--frame-type'] 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 curr_exe = SingleTemplateExecutable(workflow.cp, 'single_template', ifos=[ifo], out_dir=out_dir, tags=[tag] + tags) start = int(params[ifo + '_end_time']) end = start + 1 cseg = segments.segment([start, end]) node = curr_exe.create_node(valid_seg=cseg) 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_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_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_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_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_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_qscan_plot(workflow, ifo, trig_time, out_dir, injection_file=None, data_segments=None, time_window=100, tags=None): """ Generate a make_qscan 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. ifo: str Which interferometer are we using? trig_time: int The time of the trigger being followed up. out_dir: str Location of directory to output to injection_file: pycbc.workflow.File (optional, default=None) If given, add the injections in the file to strain before making the plot. data_segments: ligo.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. 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 100s should be fine for most cases. 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_qscan' curr_exe = PlotQScanExecutable(workflow.cp, name, ifos=[ifo], out_dir=out_dir, tags=tags) # Determine start/end times, using data segments if needed. # Begin by choosing "optimal" times start = trig_time - time_window end = trig_time + time_window node = curr_exe.create_node(valid_seg=segments.segment([start, end])) # 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 elif trig_time == -1.0: node.add_opt('--gps-start-time', int(trig_time)) node.add_opt('--gps-end-time', int(trig_time)) node.add_opt('--center-time', trig_time) caption_string = "'No trigger in %s'" % ifo node.add_opt('--plot-caption', caption_string) node.new_output_file_opt(workflow.analysis_time, '.png', '--output-file') workflow += node return node.output_files 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 # We only read data that's available. The code must handle the case # of not much data being available. if end > (data_seg[1] - pad_data): end = data_seg[1] - pad_data if start < (data_seg[0] + pad_data): start = data_seg[0] + pad_data node.add_opt('--gps-start-time', int(start)) node.add_opt('--gps-end-time', int(end)) node.add_opt('--center-time', trig_time) if injection_file is not None: node.add_input_opt('--injection-file', injection_file) node.new_output_file_opt(workflow.analysis_time, '.png', '--output-file') 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: pycbc.workflow.core.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: ligo.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 = SingleTimeFreqExecutable(workflow.cp, name, ifos=[single.ifo], out_dir=out_dir, tags=tags) # Determine start/end times, using data segments if needed. # Begin by choosing "optimal" times start = trig_time - time_window end = trig_time + time_window node = curr_exe.create_node(valid_seg=segments.segment([start, end])) node.add_input_opt('--trig-file', single) node.add_input_opt('--bank-file', bank_file) # 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 elif trig_time == -1.0: node.add_opt('--gps-start-time', int(trig_time)) node.add_opt('--gps-end-time', int(trig_time)) node.add_opt('--center-time', 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 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', 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_skipped_html(workflow, skipped_data, out_dir, tags): """ Make a html snippet from the list of skipped background coincidences """ exe = Executable(workflow.cp, 'html_snippet', ifos=workflow.ifos, out_dir=out_dir, tags=tags) node = exe.create_node() parsed_data = {} for ifo, time in skipped_data: if ifo not in parsed_data: parsed_data[ifo] = {} if time not in parsed_data[ifo]: parsed_data[ifo][time] = 1 else: parsed_data[ifo][time] = parsed_data[ifo][time] + 1 n_events = len(skipped_data) html_string = '"{} background events have been skipped '.format(n_events) html_string += 'because one of their single triggers already appears ' html_string += 'in the events followed up above. ' html_string += 'Specifically, the following single detector triggers ' html_string += 'were found in these coincidences. ' html_template = '{} event at time {} appeared {} times. ' for ifo in parsed_data: for time in parsed_data[ifo]: n_occurances = parsed_data[ifo][time] html_string += html_template.format(ifo, time, n_occurances) html_string += '"' node.add_opt('--html-text', html_string) node.add_opt('--title', '"Events were skipped"') node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file') workflow += node files = node.output_files return files