gravelamps.inference
====================

.. py:module:: gravelamps.inference

.. autoapi-nested-parse::

   Inference configuration and running

   The following are the functions which control the setup and running of a nested sampling inference
   run for lensed gravitational waveforms, including the production of lensed data and the actual
   nested sampling run. The main function is accessed via `gravelamps_inference`.

   Written by Mick Wright 2022

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Functions
---------

.. autoapisummary::

   gravelamps.inference.generate_files
   gravelamps.inference.generate_waveform_arguments
   gravelamps.inference.generate_inference_args
   gravelamps.inference.run_bilby_pipe_functions
   gravelamps.inference.main


Module Contents
---------------

.. py:function:: generate_files(config, lens_module, lens_package, lens_generation_args, injection)

   
   Generate required interpolator files, if necessary

   Will generate a dictionary containing the needed files for the interpolator. Primarily this is
   done via `gravelamps.generate_lens.main`, however,  if the specified module is capable of
   producing interpolator data directly via a function `generate_interpolator_files`, this will be
   used instead. None will be returned if no files are necessary.

   :Parameters:

       **config** : configparser.ConfigParser
           INI Configuration Parser containing lens generation settings

       **lens_module** : str
           Name of the module being used for lensing functions

       **lens_package** : ModuleType
           Module containing the lensing function

       **lens_generation_args** : Namespace
           Namespace containing commandline arguments to main function

       **injection** : bool
           Flag to determine if run is injection or analysis

   :Returns:

       **interpolator_files** : dict/None
           Contains the paths to the files needed for interpolator generation if files are needed













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.. py:function:: generate_waveform_arguments(config, args)

   
   Generate waveform arguments dictionary


   :Parameters:

       **config** : configparser.ConfigParser
           INI Configuration Parser containing waveform settings

       **args** : argparse.Namespace
           Namespace containing commandline arguments to main function

   :Returns:

       **waveform_arguments** : dict
           Arguments for the waveform generation













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.. py:function:: generate_inference_args(args, injection=False)

   
   Generate additional argument set for main function

   Creates an additional copy of the commandline arguments provided to inference in order to
   run simultaneously an injection and analysis run of lens generation.

   :Parameters:

       **args** : argparse.Namespace
           Commandline arguments passed to main inference program

       **injection** : bool, optional, default=False
           Flag to determine whether result should be an injection or analysis configuration

   :Returns:

       **inference_args** : argparse.Namespace
           Commandline argument copy with specified settings













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.. py:function:: run_bilby_pipe_functions(bilby_pipe_config)

   
   Execute bilby_pipe DAG generation functions

   Creates the DAG necessary to run the bilby_pipe aspects of the job which handle the waveform
   construction and nested sampling of the data.

   :Parameters:

       **bilby_pipe_config** : dict
           Contains configuration options for running of bilby_pipe functions














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.. py:function:: main()

   
   Generate lensed infernece run

   Configuration should be specified within provided INI file. THe function will then produce
   a complete configuration for the generation of necessary lensed interpolator data, and
   inference of signal data using the lensed waveforms. If the user specifies, this will be run
   directly, or a DAG will be generated for submission to HTCondor. If the user specifies, the
   DAG will be directly submitted to the scheduler.















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