File input/output

HDF output file handler (gwin.io.InferenceFile)

The executable gwin will write a HDF file with all the samples from each walker along with the PSDs and some meta-data about the sampler. To read the output file:

from gwin.io import InferenceFile
fp = InferenceFile("example.h5", "r")

To get all samples for distance from the first walker you can do:

samples = fp.read_samples("distance", walkers=0)
print(samples.distance)

The InferenceFile.read_samples() method includes the options to thin the samples. By default the function will return samples beginning at the end of the burn-in to the last written sample, and will use the autocorrelation length (ACL) calculated by gwin to select the indepdedent samples. You can supply thin_start, thin_end, and thin_interval to override this. To read all samples you would do:

samples = fp.read_samples("distance", walkers=0,
                          thin_start=0, thin_end=-1, thin_interval=1)
print(samples.distance)

Some standard parameters that are derived from the variable arguments (listed via fp.variable_params) can also be retrieved. For example, if fp.variable_params includes 'mass1' and 'mass2', then you can retrieve the chirp mass with:

samples = fp.read_samples("mchirp")
print(samples.mchirp)

Some standard parameters that are derived from the variable arguments (listed via fp.variable_params) can also be retrieved. For example, if fp.variable_params includes 'mass1' and 'mass2', then you can retrieve the chirp mass with:

samples = fp.read_samples("mchirp")
print(samples.mchirp)

In this case, fp.read_samples will retrieve mass1 and mass2 (since they are needed to compute chirp mass); samples.mchirp then returns an array of the chirp mass computed from mass1 and mass2.

For more information, including the list of predefined derived parameters, see the class reference for InferenceFile.

API Reference

InferenceFile(path[, mode])	A subclass of the h5py.File object that has extra functions for handling reading and writing the samples from the samplers.
InferenceTXTFile(path[, mode, delimiter])	A class that has extra functions for handling reading the samples from posterior-only TXT files.