import numpy as np
import Starfish
from Starfish import parallel
from Starfish.parallel import args
from Starfish.model import ThetaParam, PhiParam
print("THIS IS WORKING")
if args.generate:
model = parallel.OptimizeTheta(debug=True)
# Now that the different processes have been forked, initialize them
pconns, cconns, ps = parallel.initialize(model)
pars = ThetaParam.from_dict(Starfish.config["Theta"])
for ((spectrum_id, order_id), pconn) in pconns.items():
#Parse the parameters into what needs to be sent to each Model here.
pconn.send(("LNPROB", pars))
pconn.recv() # Receive and discard the answer so we can send the save
pconn.send(("SAVE", None))
# 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()
# All of the argument parsing is done in the `parallel.py` module.
import numpy as np
import Starfish
from Starfish import parallel_linear
from Starfish.parallel_linear import args
from Starfish.model import ThetaParam, PhiParam
if args.generate:
model = parallel_linear.OptimizeTheta(debug=True)
# Now that the different processes have been forked, initialize them
pconns, cconns, ps = parallel_linear.initialize(model)
pars = ThetaParam.from_dict(Starfish.config["Theta"])
for ((spectrum_id, order_id), pconn) in pconns.items():
#Parse the parameters into what needs to be sent to each Model here.
pconn.send(("LNPROB", pars))
pconn.recv() # Receive and discard the answer so we can send the save
pconn.send(("SAVE", None))
# 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()
