action='store_true', help='restart an old run') parser.add_argument('--init', metavar='FILE', help='file storing initial point') parser.add_argument('--delta', metavar='DPARAM', type=float, default=1e-3, help='fractional width about initial point') args = parser.parse_args() ts, rvs = load_data(args.rvs) pmin, pmax = cl.prior_bounds_from_data(args.nplanets, ts, rvs) ndim = 5 * args.nplanets + 4 * len(ts) # If re-starting a run, burnin = nthin, so that output continues # to be evenly-spaced if args.restart: args.nburnin = args.nthin - 1 if args.restart: pts = [] logls = [] lnprobs = [] for i in range(args.ntemps): data = np.loadtxt('%s.%02d.txt.gz' % (args.prefix, i))
parser.add_argument('--nburnin', metavar='N', type=int, default=100, help='number of initial ensembles to discard as burnin') parser.add_argument('--ntemps', metavar='N', type=int, default=20, help='number of temperatures') parser.add_argument('--nwalkers', metavar='N', type=int, default=100, help='number of walkers') parser.add_argument('--rvs', metavar='FILE', required=True, default=[], action='append', help='file of times and RV\'s') parser.add_argument('--restart', action='store_true', help='restart an old run') parser.add_argument('--init', metavar='FILE', help='file storing initial point') parser.add_argument('--delta', metavar='DPARAM', type=float, default=1e-3, help='fractional width about initial point') args=parser.parse_args() ts, rvs=load_data(args.rvs) pmin,pmax=cl.prior_bounds_from_data(args.nplanets, ts, rvs) ndim = 5*args.nplanets + 4*len(ts) # If re-starting a run, burnin = nthin, so that output continues # to be evenly-spaced if args.restart: args.nburnin = args.nthin - 1 if args.restart: pts=[] logls=[] lnprobs=[] for i in range(args.ntemps): data=np.loadtxt('%s.%02d.txt.gz'%(args.prefix, i))
parser.add_argument('--ntemps', metavar='N', default=20, type=int, help='number of temperatures') args=parser.parse_args() ts=[] rvs=[] for f in args.rvs: data=np.loadtxt(f) ts.append(data[:,0]) rvs.append(data[:,1]) nobs = len(ts) npl = args.npl newnpl = npl + 1 pmin,pmax = cl.prior_bounds_from_data(newnpl, ts, rvs) chain = pr.Parameters(arr=np.loadtxt(args.input)[-args.nwalkers:, 2:], npl=npl, nobs=nobs) newchain = pr.Parameters(arr=np.zeros((args.nwalkers, chain.shape[1]+5)), npl=newnpl, nobs=nobs) newchain[:, :-5] = chain newks = newchain.K newks[:, -1] = draw_logarithmic(pmin.K[0], pmax.K[0], size=args.nwalkers) newchain.K = newks newes = newchain.e newes[:,-1] = nr.uniform(low=0.0, high=1.0, size=args.nwalkers) newchain.e = newes newchis = newchain.chi
help='number of temperatures') args = parser.parse_args() ts = [] rvs = [] for f in args.rvs: data = np.loadtxt(f) ts.append(data[:, 0]) rvs.append(data[:, 1]) nobs = len(ts) npl = args.npl newnpl = npl + 1 pmin, pmax = cl.prior_bounds_from_data(newnpl, ts, rvs) chain = pr.Parameters(arr=np.loadtxt(args.input)[-args.nwalkers:, 2:], npl=npl, nobs=nobs) newchain = pr.Parameters(arr=np.zeros((args.nwalkers, chain.shape[1] + 5)), npl=newnpl, nobs=nobs) newchain[:, :-5] = chain newks = newchain.K newks[:, -1] = draw_logarithmic(pmin.K[0], pmax.K[0], size=args.nwalkers) newchain.K = newks newes = newchain.e