gw.transforms.detector_transforms.SampleCalibrationParameters
gw.transforms.detector_transforms.SampleCalibrationParameters(
ifo_list,
data_domain,
calibration_envelope,
num_calibration_curves,
num_calibration_nodes,
correction_type='data',
)Expand out a waveform using several detector calibration draws. These multiple draws are intended to be used for marginalizing over calibration uncertainty.
The calibration parameters are not known precisely, rather they are assumed to be normally distributed, with mean 0 and standard deviation determined by the “calibration envelope”, which varies from event to event.
Therefore, for each detector waveform, this transform draws a collection of \(N\) calibration curves \(\{(\delta A^n(f), \delta \phi^n(f))\}_{n=1}^N\) according to a calibration envelope, and applies them to generate \(N\) observed waveforms \(\{h^n_{ obs}(f)\}\). This is intended to be used for marginalizing over the calibration uncertainty when evaluating the likelihood for importance sampling.
This transform should be followed by ApplyCalibrationToWaveform to apply the sampled calibration curves to the waveform.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| ifo_list | InterferometerList | List of Interferometers present in the analysis. | required |
| data_domain | Domain | Domain on which data is defined. | required |
| calibration_envelope | dict | Dictionary of the form {"H1": filepath, "L1": filepath}, where the filepaths are strings pointing to “.txt” files containing calibration envelopes. |
required |
| num_calibration_curves | int | Number of calibration curves to sample. | required |
| num_calibration_nodes | int | Number of log-spaced frequency nodes for the spline. | required |
| correction_type | str = "data" | Whether envelopes are over eta (“data”) or alpha (“template”). | 'data' |
Attributes
| Name | Description |
|---|---|
| calibration_envelope | |
| calibration_prior | |
| data_domain | |
| ifo_list | |
| num_calibration_curves |