dags.layers.inspiral module

dags.layers.inspiral.add_ranking_stat_file_options(config, svd_bin=None, transfer_only=False)

Return a list of options relating to files used for terms in the ranking statistic, including:

• dtdphi

• iDQ timeseries

if transfer_only is True, do not add options to programs, instead, only use these files as inputs for Condor file transfer. This is required for jobs that require these files, as their paths are tracked through the ranking stat, so Condor needs to be aware of these files when not relying on a shared file system.

dags.layers.inspiral.aggregate_layer(config, dag, trigger_cache, dist_stat_cache=None)

dags.layers.inspiral.calc_expected_snr_layer(config, dag, psd_cache, injection_cache)

dags.layers.inspiral.calc_likelihood_layer(config, dag, trigger_cache, dist_stat_cache)

dags.layers.inspiral.calc_pdf_layer(config, dag, dist_stat_cache)

dags.layers.inspiral.checkerboard_layer(config, dag, ref_psd_cache, svd_bank_cache)

dags.layers.inspiral.cluster_layer(config, dag, trigger_cache, injection_cache)

dags.layers.inspiral.collect_metrics_layer(config, dag)

dags.layers.inspiral.compute_far_layer(config, dag, trigger_cache, pdf_cache)

dags.layers.inspiral.count_events_layer(config, dag, dist_stat_cache)

dags.layers.inspiral.create_prior_layer(config, dag, svd_bank_cache, median_psd_cache, dist_stat_cache=None)

dags.layers.inspiral.filter_injections_layer(config, dag, ref_psd_cache, svd_bank_cache)

dags.layers.inspiral.filter_injections_online_layer(config, dag, svd_bank_cache, dist_stat_cache, zerolag_pdf_cache, marg_pdf_cache)

dags.layers.inspiral.filter_layer(config, dag, ref_psd_cache, svd_bank_cache)

dags.layers.inspiral.filter_online_layer(config, dag, svd_bank_cache, dist_stat_cache, zerolag_pdf_cache, marg_pdf_cache)

dags.layers.inspiral.find_injections_layer(config, dag, trigger_db_cache)

dags.layers.inspiral.ifo_to_string(ifos)

Given a list of ifos, converts this to a string.

dags.layers.inspiral.layers()

dags.layers.inspiral.marginalize_layer(config, dag, prior_cache, dist_stat_cache)

dags.layers.inspiral.marginalize_online_layer(config, dag, marg_pdf_cache)

dags.layers.inspiral.marginalize_pdf_layer(config, dag, pdf_cache)

dags.layers.inspiral.match_injections_layer(config, dag, injection_cache)

dags.layers.inspiral.mchirp_range_to_bins(min_mchirp, max_mchirp, svd_metadata)

Given a range of chirp masses and the SVD metadata, determine and return the SVD bins that overlap.

dags.layers.inspiral.measure_lnlr_cdf_layer(config, dag, dist_stats_cache, injection_cache)

dags.layers.inspiral.plot_analytic_vt_layer(config, dag, trigger_cache, pdf_cache, lnlr_cdf_cache)

dags.layers.inspiral.plot_background_layer(config, dag, trigger_cache, post_pdf_cache)

dags.layers.inspiral.plot_bin_background_layer(config, dag, marg_dist_stat_cache)

dags.layers.inspiral.plot_events_layer(config, dag)

dags.layers.inspiral.plot_horizon_distance_layer(config, dag, marg_dist_stat_caches)

dags.layers.inspiral.plot_sensitivity_layer(config, dag, trigger_cache)

dags.layers.inspiral.plot_summary_layer(config, dag, trigger_cache, post_pdf_cache)

dags.layers.inspiral.split_bank_layer(config, dag, psd_cache, bank_cache)

dags.layers.inspiral.split_injections_layer(config, dag)

dags.layers.inspiral.svd_bank_layer(config, dag, median_psd_cache, split_bank_cache=None)

dags.layers.inspiral.time_to_num_split_injections(span, time_per_split=20000)

Determine how many injection splits given analysis start/end times.

dags.layers.inspiral.track_noise_layer(config, dag)

dags.layers.inspiral.upload_events_layer(config, dag)

dags.layers.inspiral.upload_pastro_layer(config, dag, marg_pdf_cache)