def main():
Log.set_loglevel(logging.DEBUG)
prior = Gaussian(Sigma=eye(2) * 100)
posterior = OzonePosterior(prior,
logdet_alg="scikits",
solve_method="scikits")
proposal_cov = diag([4.000000000000000e-05, 1.072091680000000e+02])
mcmc_sampler = StandardMetropolis(posterior, scale=1.0, cov=proposal_cov)
start = asarray([-11.35, -13.1])
mcmc_params = MCMCParams(start=start, num_iterations=5000)
chain = MCMCChain(mcmc_sampler, mcmc_params)
chain.append_mcmc_output(StatisticsOutput(print_from=1, lag=1))
home = expanduser("~")
folder = os.sep.join([home, "sample_ozone_posterior_average_serial"])
store_chain_output = StoreChainOutput(folder)
chain.append_mcmc_output(store_chain_output)
loaded = store_chain_output.load_last_stored_chain()
if loaded is None:
logging.info("Running chain from scratch")
else:
logging.info("Running chain from iteration %d" % loaded.iteration)
chain = loaded
chain.run()
f = open(folder + os.sep + "final_chain", "w")
dump(chain, f)
f.close()
def test_log_det_ozone_shogun_exact(self):
o = OzonePosterior()
kappa = 2 ** (-13.1)
Q = o.create_Q_matrix(kappa)
self.assertAlmostEqual(OzonePosterior.log_det_shogun_exact(Q),
2.317769370813052e+06,
delta=1)
def __init__(self, aggregator, ozone_posterior, tau, kappa):
IndependentJob.__init__(self, aggregator)
self.ozone_posterior = OzonePosterior(ozone_posterior.prior,
ozone_posterior.logdet_method,
ozone_posterior.solve_method)
self.tau = tau
self.kappa = kappa
def test_log_likelihood_scikits_exact(self):
tau = 2 ** (-11.35)
kappa = 2 ** (-13.1)
o = OzonePosterior(prior=None, logdet_method="scikits",
solve_method="scikits")
self.assertAlmostEqual(o.log_likelihood(tau, kappa),
- 9.336375798558606e+05,
delta=0.001)
def test_load_data(self):
OzonePosterior()
