def run_opti():
current_path = os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe())))
# generate the directory
apts = current_path + "/allpoints"
if not os.path.exists(apts):
os.makedirs(apts)
# create the stop file
stp = current_path + "allpoints/stop.dat"
stp_path = Path(stp)
if not stp_path.is_file():
stop = 0
fout = open("allpoints/stop.dat", 'w')
fout.write(str(stop) + "\n")
fout.close()
while stop == 0:
# DOGS_standalone() will first generate the initial points, then run alpha-DOGS algorithm.
DOGS_standlone()
# The "solver_lorenz" function will read from "pts_to_eval" and generate a file named "surr_J_new.dat"
# containing all information about function evaluation.
dogs.solver_lorenz()
# Read stop file
stop = int(np.loadtxt("allpoints/stop.dat"))
print('stop = ', stop)
return
stp_path = Path(stp)
if not stp_path.is_file():
stop = 0
fout = open("allpoints/stop.dat", 'w')
fout.write(str(stop) + "\n")
fout.close()
while stop == 0:
# DOGS_standalone() will first generate the initial points, then run alpha-DOGS algorithm.
DOGS_standlone()
# The "solver_lorenz" function will read from "pts_to_eval" and generate a file named "surr_J_new.dat"
# containing all information about function evaluation.
dogs.solver_lorenz()
# Read stop file
stop = int(np.loadtxt("allpoints/stop.dat"))
print('stop = ', stop)
return
################################################################################################################
#run_opti()
#DOGS_standlone()
dogs.solver_lorenz()
# Delete the directory of allpoints
#current_path = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
#shutil.rmtree(current_path + "/allpoints")