dingo.pipe package

Subpackages

• dingo.pipe.nodes package
  • Submodules
  • dingo.pipe.nodes.generation_node module
    • GenerationNode
      • GenerationNode.event_data_file
      • GenerationNode.executable
      • GenerationNode.job_name
      • GenerationNode.setup_arguments()
  • dingo.pipe.nodes.importance_sampling_node module
    • ImportanceSamplingNode
      • ImportanceSamplingNode.executable
      • ImportanceSamplingNode.request_memory
      • ImportanceSamplingNode.result_file
  • dingo.pipe.nodes.merge_node module
    • MergeNode
      • MergeNode.executable
      • MergeNode.result_file
      • MergeNode.run_node_on_osg
  • dingo.pipe.nodes.pe_summary_node module
    • PESummaryNode
      • PESummaryNode.run_node_on_osg
  • dingo.pipe.nodes.plot_node module
    • PlotNode
      • PlotNode.executable
      • PlotNode.run_node_on_osg
    • PlotPPNode
      • PlotPPNode.executable
      • PlotPPNode.request_memory
  • dingo.pipe.nodes.sampling_node module
    • SamplingNode
      • SamplingNode.executable
      • SamplingNode.result_file
      • SamplingNode.samples_file
  • Module contents

Submodules

dingo.pipe.create_injections module

dingo.pipe.dag_creator module

dingo.pipe.dag_creator.generate_dag(inputs)

dingo.pipe.dag_creator.get_parallel_list(inputs)

dingo.pipe.dag_creator.get_trigger_time_list(inputs)

Returns a list of GPS trigger times for each data segment

dingo.pipe.data_generation module

class dingo.pipe.data_generation.DataGenerationInput(args, unknown_args, create_data=True)

Bases: DataGenerationInput

create_data_dingo_injection(args)

Adaptation of create_data to use Dingo signal models rather than Bilby.

First, executes create_data but without any requested injections. This creates a noise-only dataset.

Second, calls _inject_dingo_signal to generate the Dingo signal waveform and add it to the noisy data within the interferometers.

property event_data_file

property importance_sampling_updates

property interferometers

A bilby.gw.detector.InterferometerList

property prior_dict_updates

The input prior_dict from the ini (if given)

Note, this is not the bilby prior (see self.priors for that), this is a key-val dictionary where the val’s are strings which are converting into bilby priors in `_get_prior

save_hdf5()

Save frequency-domain strain and ASDs as DingoDataset HDF5 format.

This method will also save the PSDs as .txt files in the data directory for easy reading by pesummary and Bilby.

dingo.pipe.data_generation.create_generation_parser()

Data generation parser creation

dingo.pipe.data_generation.main()

Data generation main logic

dingo.pipe.default_settings module

dingo.pipe.dingo_result module

dingo.pipe.dingo_result.main()

dingo.pipe.importance_sampling module

Script to importance sample based on Dingo samples. Based on bilby_pipe data analysis script.

class dingo.pipe.importance_sampling.ImportanceSamplingInput(args, unknown_args)

Bases: Input

property calibration_marginalization_kwargs

property importance_sampling_settings

property prior_dict_updates

The input prior_dict from the ini (if given)

Note, this is not the bilby prior (see self.priors for that), this is a key-val dictionary where the val’s are strings which are converting into bilby priors in `_get_prior

property priors

Read in and compose the prior at run-time

property request_memory

run_sampler()

dingo.pipe.importance_sampling.create_sampling_parser()

Data analysis parser creation

dingo.pipe.importance_sampling.main()

Data analysis main logic

dingo.pipe.main module

class dingo.pipe.main.MainInput(args, unknown_args, importance_sampling_updates, perform_checks=True)

Bases: MainInput

check_accounting()

check_injection()

Check injection behaviour

If injections are requested, either use the injection-dict, injection-file, or create an injection-file

property prior_dict_updates

The input prior_dict from the ini (if given)

Note, this is not the bilby prior (see self.priors for that), this is a key-val dictionary where the val’s are strings which are converting into bilby priors in `_get_prior

property request_cpus_importance_sampling

dingo.pipe.main.fill_in_arguments_from_model(args, perform_arg_checks=True)

dingo.pipe.main.main()

dingo.pipe.main.write_complete_config_file(parser, args, inputs, input_cls=<class 'dingo.pipe.main.MainInput'>)

dingo.pipe.parser module

class dingo.pipe.parser.StoreBoolean(option_strings, dest, nargs=None, const=None, default=None, type=None, choices=None, required=False, help=None, metavar=None)

Bases: Action

argparse class for robust handling of booleans with configargparse

When using configargparse, if the argument is setup with action=”store_true”, but the default is set to True, then there is no way, in the config file to switch the parameter off. To resolve this, this class handles the boolean properly.

dingo.pipe.parser.create_parser(top_level=True, usage=None)

Creates the BilbyArgParser for dingo_pipe

Parameters:

top_level – If true, parser is to be used at the top-level with requirement checking etc., else it is an internal call and will be ignored.

Returns:

parser – Argument parser

Return type:

BilbyArgParser instance

dingo.pipe.plot module

dingo.pipe.plot.create_parser()

Generate a parser for the plot script

Returns:

parser – A parser with all the default options already added

Return type:

BilbyArgParser

dingo.pipe.plot.main()

dingo.pipe.pp_test module

dingo.pipe.pp_test.create_parser()

dingo.pipe.pp_test.get_basename(args)

dingo.pipe.pp_test.get_results_filenames(args)

dingo.pipe.pp_test.main(args=None)

dingo.pipe.sampling module

Script to sample from a Dingo model. Based on bilby_pipe data analysis script.

class dingo.pipe.sampling.SamplingInput(args, unknown_args)

Bases: Input

property density_recovery_settings

run_sampler()

dingo.pipe.sampling.create_sampling_parser()

Data analysis parser creation

dingo.pipe.sampling.main()

Data analysis main logic

dingo.pipe.utils module

dingo.pipe.utils.dict_to_string(d)

Convert a dictionary to a string representation.

Module contents