SamplesDict class

pesummary’s gw package provides extra functionality to the core pesummary.utils.samples_dict.SamplesDict class. For details about initializing the SamplesDict class and using the core SamplesDict properties, see the core SamplesDict docs.

Parameter descriptions

pesummary provides a set of parameter descriptions for most gravitational wave specific parameters (see here). You can access these descriptions directly from the SamplesDict class,

>>> from pesummary.utils.samples_dict import SamplesDict
>>> samplesdict = SamplesDict.from_file("path_to_file.hdf5")
>>> parameters = samplesdict.keys()
>>> print(parameters[0])
'mass_1'
>>> print(parameters[0].description)
the detector-frame (redshifted) mass of the heavier object

Source classifications

pesummary provides wrappers for the PEPredicates and p-astro packages to calculate classification probabilities from the samples. We may calculate the classification probabilities with,

>>> from pesummary.utils.samples_dict import SamplesDict
>>> samplesdict = SamplesDict.from_file("path_to_file.hdf5")
>>> samplesdict.classification()
{'default': {'BNS': 0.0, 'NSBH': 0.0, 'BBH': 1.0, 'MassGap': 0.0, 'HasNS': 0.0, 'HasRemnant': 1.0}, 'population': {'BNS': 0.0, 'NSBH': 0.0, 'BBH': 1.0, 'MassGap': 0.0, 'HasNS': 0.0, 'HasRemnant': 1.0}}

Where the default classification is generated by using the samples directly, and the population classification is generated by reweighing the samples to a population based prior.