'cannot init from more than one observatory and one planet')
pts = Parameters(np.zeros((args.ntemps, args.nwalkers, ndim)))
pts.V = np.random.normal(p0.V,
p0.sigma0 * args.delta,
size=pts.V.shape[0:2])
pts.sigma0 = np.random.lognormal(np.log(p0.sigma0),
args.delta,
size=pts.sigma0.shape[0:2])
pts.sigma = np.random.lognormal(np.log(p0.sigma),
args.delta,
size=pts.sigma.shape[0:2])
pts.tau = np.random.lognormal(np.log(p0.tau),
args.delta,
size=pts.tau.shape[0:2])
pts.K = np.random.normal(p0.K,
p0.sigma0 * args.delta,
size=pts.K.shape[0:2])
pts.n = np.random.lognormal(np.log(p0.n),
args.delta,
size=pts.n.shape[0:2])
pts.chi = np.random.normal(p0.chi, args.delta, size=pts.chi.shape[0:2])
pts.e = np.random.normal(p0.e, args.delta, size=pts.e.shape[0:2])
pts.omega = np.random.normal(p0.omega,
args.delta,
size=pts.omega.shape[0:2])
logls = None
lnprobs = None
header = pts.header[0] + ' logl logp' + pts.header[1:]
for i in range(args.ntemps):
with GzipFile('%s.%02d.txt.gz' % (args.prefix, i), 'w') as out:
logls.append(data[-args.nwalkers:,0])
lnprobs.append(data[-args.nwalkers:,1]+logls[-1])
pts=np.array(pts)
logls=np.array(logls)
lnprobs=np.array(lnprobs)
elif args.init is not None:
p0=Parameters(np.loadtxt(args.init))
if len(ts) > 1 or args.nplanets > 1:
raise NotImplementedError('cannot init from more than one observatory and one planet')
pts=Parameters(np.zeros((args.ntemps, args.nwalkers, ndim)))
pts.V = np.random.normal(p0.V, p0.sigma0*args.delta, size=pts.V.shape[0:2])
pts.sigma0 = np.random.lognormal(np.log(p0.sigma0), args.delta, size=pts.sigma0.shape[0:2])
pts.sigma = np.random.lognormal(np.log(p0.sigma), args.delta, size=pts.sigma.shape[0:2])
pts.tau = np.random.lognormal(np.log(p0.tau), args.delta, size=pts.tau.shape[0:2])
pts.K = np.random.normal(p0.K, p0.sigma0*args.delta, size=pts.K.shape[0:2])
pts.n = np.random.lognormal(np.log(p0.n), args.delta, size=pts.n.shape[0:2])
pts.chi = np.random.normal(p0.chi, args.delta, size=pts.chi.shape[0:2])
pts.e = np.random.normal(p0.e, args.delta, size=pts.e.shape[0:2])
pts.omega = np.random.normal(p0.omega, args.delta, size=pts.omega.shape[0:2])
logls=None
lnprobs=None
header = pts.header[0] + ' logl logp' + pts.header[1:]
for i in range(args.ntemps):
with GzipFile('%s.%02d.txt.gz'%(args.prefix, i), 'w') as out:
out.write(header)
else:
pts=cl.generate_initial_sample(pmin, pmax, args.ntemps, args.nwalkers)
logls=None
lnprobs=None
