Crash course

Example: how to sample a gravitational wave source posterior using Nautilus:

from cogwheel import data
from cogwheel import sampling
from cogwheel.posterior import Posterior

parentdir = 'example'  # Directory that will contain parameter estimation runs

eventname, mchirp_guess = 'GW150914', 30
approximant = 'IMRPhenomXPHM'
prior_class = 'CartesianIntrinsicIASPrior'

filenames, detector_names, tgps = data.download_timeseries(eventname)
event_data = data.EventData.from_timeseries(
    filenames, eventname, detector_names, tgps)

post = Posterior.from_event(event_data, mchirp_guess, approximant, prior_class)

sampler = sampling.Nautilus(post, run_kwargs=dict(n_live=1000))

rundir = sampler.get_rundir(parentdir)
sampler.run(rundir)  # Will take a while

Load and plot the samples:

import matplotlib.pyplot as plt
import pandas as pd
from cogwheel import gw_plotting

samples = pd.read_feather(rundir/sampling.SAMPLES_FILENAME)
gw_plotting.CornerPlot(samples,
                       params=sampler.sampled_params,
                       tail_probability=1e-4).plot()
plt.savefig(rundir/f'{eventname}.pdf', bbox_inches='tight')