run_pypolychord.py

from numpy import pi, log, sqrt
import pypolychord
from pypolychord.settings import PolyChordSettings
from pypolychord.priors import UniformPrior

#| Define a four-dimensional spherical gaussian likelihood,
#| width sigma=0.1, centered on the 0 with one derived parameter.
#| The derived parameter is the squared radius

nDims = 4
nDerived = 1
sigma = 0.1

def likelihood(theta):
    """ Simple Gaussian Likelihood"""

    nDims = len(theta)
    r2 = sum(theta**2)
    logL = -log(2*pi*sigma*sigma)*nDims/2.0
    logL += -r2/2/sigma/sigma

    return logL, [r2]

#| Define a box uniform prior from -1 to 1

def prior(hypercube):
    """ Uniform prior from [-1,1]^D. """
    return UniformPrior(-1, 1)(hypercube)

#| Optional dumper function giving run-time read access to
#| the live points, dead points, weights and evidences

def dumper(live, dead, logweights, logZ, logZerr):
    print("Last dead point:", dead[-1])

#| Initialise the settings

settings = PolyChordSettings(nDims, nDerived)
settings.file_root = 'gaussian'
settings.nlive = 200
settings.do_clustering = True
settings.read_resume = False

#| Run PolyChord

output = pypolychord.run_polychord(likelihood, nDims, nDerived, settings, prior, dumper)

#| Create a paramnames file

paramnames = [('p%i' % i, r'\theta_%i' % i) for i in range(nDims)]
paramnames += [('r*', 'r')]
output.make_paramnames_files(paramnames)

#| Make a getdist plot

try:
    import getdist.plots
    posterior = output.posterior
    g = getdist.plots.getSubplotPlotter()
    g.triangle_plot(posterior, filled=True)
    g.export('posterior.pdf')
except ImportError:
    print("Install matplotlib and getdist for plotting examples")