cov = np.load('opt_jump.npy')
print("Found a local optimal jump matrix.")
except FileNotFoundError:
print("No optimal jump matrix found, using diagonal jump matrix.")
sampler = StateSampler(lnprob,
p0,
cov,
query_lnprob=query_lnprob,
acceptfn=acceptfn,
rejectfn=rejectfn,
debug=True,
outdir=Starfish.routdir)
p, lnprob, state = sampler.run_mcmc(p0,
N=args.samples,
incremental_save=args.incremental_save)
print("Final", p)
sampler.write()
# Kill all of the orders
for pconn in pconns.values():
pconn.send(("FINISH", None))
pconn.send(("DIE", None))
# Join on everything and terminate
for p in ps.values():
p.join()
p.terminate()
def rejectfn():
print("Calling rejectfn")
for ((spectrum_id, order_id), pconn) in pconns.items():
pconn.send(("DECIDE", False))
from Starfish.samplers import StateSampler
start = Starfish.config["Theta"]
p0 = np.array(start["grid"] + [start["vz"], start["vsini"], start["logOmega"]])
jump = Starfish.config["Theta_jump"]
cov = np.diag(np.array(jump["grid"] + [jump["vz"], jump["vsini"], jump["logOmega"]])**2)
sampler = StateSampler(lnprob, p0, cov, query_lnprob=query_lnprob, acceptfn=acceptfn, rejectfn=rejectfn, debug=True, outdir=Starfish.routdir)
p, lnprob, state = sampler.run_mcmc(p0, N=args.samples)
print("Final", p)
sampler.write()
# Kill all of the orders
for pconn in pconns.values():
pconn.send(("FINISH", None))
pconn.send(("DIE", None))
# Join on everything and terminate
for p in ps.values():
p.join()
p.terminate()
import sys;sys.exit()
def rejectfn():
print("Calling rejectfn")
for ((spectrum_id, order_id), pconn) in pconns.items():
pconn.send(("DECIDE", False))
from Starfish.samplers import StateSampler
start = Starfish.config["Theta"]
p0 = np.array(start["grid"] + [start["vz"], start["vsini"], start["logOmega"]])
jump = Starfish.config["Theta_jump"]
cov = np.diag(np.array(jump["grid"] + [jump["vz"], jump["vsini"], jump["logOmega"]])**2)
sampler = StateSampler(lnprob, p0, cov, query_lnprob=query_lnprob, acceptfn=acceptfn, rejectfn=rejectfn, debug=True, outdir=Starfish.routdir)
p, lnprob, state = sampler.run_mcmc(p0, N=args.samples)
print("Final", p)
sampler.write()
# Kill all of the orders
for pconn in pconns.values():
pconn.send(("FINISH", None))
pconn.send(("DIE", None))
# Join on everything and terminate
for p in ps.values():
p.join()
p.terminate()
import sys;sys.exit()
start = Starfish.config["Theta"]
p0 = np.array(start["grid"] + [start["vz"], start["vsini"], start["logOmega"]])
jump = Starfish.config["Theta_jump"]
cov = np.diag(np.array(jump["grid"] + [jump["vz"], jump["vsini"], jump["logOmega"]])**2)
if args.use_cov:
try:
cov = np.load('opt_jump.npy')
print("Found a local optimal jump matrix.")
except FileNotFoundError:
print("No optimal jump matrix found, using diagonal jump matrix.")
sampler = StateSampler(lnprob, p0, cov, query_lnprob=query_lnprob, acceptfn=acceptfn, rejectfn=rejectfn, debug=True, outdir=Starfish.routdir)
p, lnprob, state = sampler.run_mcmc(p0, N=args.samples, incremental_save=args.incremental_save)
print("Final", p)
sampler.write()
# Kill all of the orders
for pconn in pconns.values():
pconn.send(("FINISH", None))
pconn.send(("DIE", None))
# Join on everything and terminate
for p in ps.values():
p.join()
p.terminate()
import sys;sys.exit()
