gravelamps.lensing.strong_event_handling

Gravelamps Strong Lensing Event Handling

Following are functions that are model agnostic and used to handle interactions between strong lensing events and the model specific functions within the rest of the module.

Routines

get_event_signal

Generate interferometer signal data from provided information

get_model_generator

Create Waveform Generator for specific model to be used for likelihood calculations

generate_source_position_interpolator

Generate interpolator function which maps relative magnification to source position.

observables_to_model_parameters

Convert lensing observables to model specific parameters

generate_probability_interpolator

Generate interpolator function object mapping source position and redshifted lnes mass to the probability of both occurring.

Functions

get_event_signal(args, event_data)

Generate interferometer signal data from provided information

get_model_generator(args, module, event_data)

Create Waveform Generator for specific model to be used for likelihood calculations

generate_source_position_interpolator(module, ...[, plot])

Generate interpolator function which maps relative magnification to source position.

observables_to_model_parameters(module, args, ...)

Convert lensing observables to model specific parameters

generate_probability_interpolator(...[, ...])

Generate interpolator function object mapping source position and redshifted lnes mass to the

Module Contents

gravelamps.lensing.strong_event_handling.get_event_signal(args, event_data)

Generate interferometer signal data from provided information

User flags also allow the plotting of interferometric data and in the case of injections, the plotting of the true signal data.

Parameters:
argsargparse.Namespace

Object containing commandline arguments to the program

event_datadict

Information about the event

Returns:
interferometersbilby.gw.detector.InterferometerList

Object containing interferometer data for specified detectors

gravelamps.lensing.strong_event_handling.get_model_generator(args, module, event_data)

Create Waveform Generator for specific model to be used for likelihood calculations

Flags will also allow the plotting of the frequency domain strain for injections

Parameters:
argsargparse.Namespace

Object containing commandline arguments to the program

modulemodule

Module containing lens model functions

event_datadict

Information about the event

Returns:
lensed_waveform_generatorgravelamps.lensing.waveform_generator.SingleImageGenerator

Object containing signal data

gravelamps.lensing.strong_event_handling.generate_source_position_interpolator(module, source_position_array, plot=False)

Generate interpolator function which maps relative magnification to source position.

Parameters:
modulemodule

Module containing lens model functions

source_position_arrayArrayLike

Source position range over which to generate interpolator

plotbool, optional

Generate plot of data that forms interpolator. Default is false

Returns:
source_position_interpolatorscipy.interpolate.interp1d

Interpolating function taking relative magnification and returning source position

gravelamps.lensing.strong_event_handling.observables_to_model_parameters(module, args, relative_magnification_data, time_delay_data)

Convert lensing observables to model specific parameters

Parameters:
modulemodule

Module containing lens model functions

argsargparse.Namespace

Object containing commandline arguments to the program

relative_magnification_dataArrayLike

Sample relative magnification values

time_delay_dataArrayLike

Sample time delay values

Returns:
source_position_dataArrayLike

Calculated sample source position values

mass_dataArrayLike

Calculated sample redshited lens mass values

gravelamps.lensing.strong_event_handling.generate_probability_interpolator(source_position_data, mass_data, number_of_bins=30, plot=False, model=None)

Generate interpolator function object mapping source position and redshifted lnes mass to the probability of both occurring.

This is done by taking a normalised histogram of the occurrances of each parameter in the data. User flag allows the plotting of the histogram data that forms the basis fo the interpolator.