gw.prior.BBHExtrinsicPriorDict
gw.prior.BBHExtrinsicPriorDict()This class is the same as BBHPriorDict except that it does not require mass parameters.
It also contains a method for estimating the standardization parameters.
TODO: * Add support for zenith/azimuth * Defaults?
Methods
| Name | Description |
|---|---|
| default_conversion_function | |
| mean_std | Calculate the mean and standard deviation over the prior. |
default_conversion_function
gw.prior.BBHExtrinsicPriorDict.default_conversion_function(sample)mean_std
gw.prior.BBHExtrinsicPriorDict.mean_std(
keys=[],
sample_size=50000,
force_numerical=False,
)Calculate the mean and standard deviation over the prior.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| keys | A list of desired parameter names | [] |
|
| sample_size | For nonanalytic priors, number of samples to use to estimate the result. | 50000 |
|
| force_numerical | Whether to force a numerical estimation of result, even when analytic results are available (useful for testing) | False |
|
| Returns | required | ||
| TODO | required |