bilby.gw.waveform_generator.GWSignalWaveformGenerator

class bilby.gw.waveform_generator.GWSignalWaveformGenerator(spinning=True, eccentric=False, tidal=False, **kwargs)[source]

Bases: WaveformGenerator

A wrapper to the `gwsignal waveform generator`_ that allows for use of arbitrary waveforms implemented as gwsignal generators and caches the generator between calls.

This wrapper allows sets of parameters to be enabled/disabled. When, e.g., spinning=False all spin parameters will be fixed to zero.

Parameters:

spinning: bool: Whether to model spins of the individual objects (default=True)
eccentric: bool: Whether to model orbital eccentricity (default=False)
tidal: bool: Whether to model tidal deformability of the individual objects (default=False)
sampling_frequency: float, optional: The sampling frequency
duration: float, optional: Time duration of data
start_time: float, optional: Starting time of the time array
parameters: dict, optional: Initial values for the parameters
parameter_conversion: func, optional: Function to convert from sampled parameters to parameters of the waveform generator. The default value is the identity, i.e., it leaves the parameters unaffected.
waveform_arguments: dict, optional: A dictionary of fixed keyword arguments to pass to the waveform generator. There is one required waveform argument waveform_approximant.
.. gwsignal waveform generator: https://docs.ligo.org/lscsoft/lalsuite/lalsimulation/classlalsimulation_1_1gwsignal_1_1core_1_1waveform_1_1_gravitational_wave_generator.html # noqa

__init__(spinning=True, eccentric=False, tidal=False, **kwargs)[source]

The base waveform generator class.

Parameters:

sampling_frequency: float, optional

The sampling frequency

duration: float, optional

Time duration of data

start_time: float, optional

Starting time of the time array

frequency_domain_source_model: func, optional

A python function taking some arguments and returning the frequency domain strain. Note the first argument must be the frequencies at which to compute the strain

time_domain_source_model: func, optional

A python function taking some arguments and returning the time domain strain. Note the first argument must be the times at which to compute the strain

parameters: dict, optional

Initial values for the parameters

parameter_conversion: func, optional

Function to convert from sampled parameters to parameters of the waveform generator. Default value is the identity, i.e. it leaves the parameters unaffected.

waveform_arguments: dict, optional

A dictionary of fixed keyword arguments to pass to either frequency_domain_source_model or time_domain_source_model.

Note: the arguments of frequency_domain_source_model (except the first, which is the frequencies at which to compute the strain) will be added to the WaveformGenerator object and initialised to None.

__call__(*args, **kwargs): Call self as a function.

Methods

`__init__`([spinning, eccentric, tidal])	The base waveform generator class.
`frequency_domain_strain`(parameters)	Wrapper to source_model.
`time_domain_strain`(parameters)	Wrapper to source_model.

Attributes

`defaults`
`generator_pickles`
`parameters`	The dictionary of parameters for source model.

frequency_domain_strain(parameters)[source]

Wrapper to source_model.

Converts self.parameters with self.parameter_conversion before handing it off to the source model. Automatically refers to the time_domain_source model via NFFT if no frequency_domain_source_model is given.

Parameters:

parameters: dict, optional: Parameters to evaluate the waveform for, this overwrites self.parameters. If not provided will fall back to self.parameters.

Returns:

array_like: The frequency domain strain for the given set of parameters

Raises:

RuntimeError: If no source model is given

property parameters

The dictionary of parameters for source model.

Returns:

dict: The dictionary of parameter key-value pairs

time_domain_strain(parameters)[source]

Wrapper to source_model.

Converts self.parameters with self.parameter_conversion before handing it off to the source model. Automatically refers to the frequency_domain_source model via INFFT if no frequency_domain_source_model is given.

Parameters:

parameters: dict, optional: Parameters to evaluate the waveform for, this overwrites self.parameters. If not provided will fall back to self.parameters.

Returns:

array_like: The time domain strain for the given set of parameters

Raises:

RuntimeError: If no source model is given