'stop_partial_fvec_eval': True
} # Should alloc preempt evals
}
# end_alloc_specs_rst_tag
persis_info = add_unique_random_streams(persis_info, nworkers + 1)
persis_info_safe = deepcopy(persis_info)
exit_criteria = {'sim_max': budget, 'elapsed_wallclock_time': 300}
# Perform the run
H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info,
alloc_specs, libE_specs)
if is_master:
assert flag == 0
save_libE_output(H, persis_info, __file__, nworkers)
# Perform the run but not stopping on NaNs
alloc_specs['user'].pop('stop_on_NaNs')
persis_info = deepcopy(persis_info_safe)
H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info,
alloc_specs, libE_specs)
if is_master:
assert flag == 0
# Perform the run also not stopping on partial fvec evals
alloc_specs['user'].pop('stop_partial_fvec_eval')
persis_info = deepcopy(persis_info_safe)
H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info,
alloc_specs, libE_specs)
if is_master:
gen_specs['user'].update({
'grtol': 1e-4,
'gatol': 1e-4,
'frtol': 1e-15,
'fatol': 1e-15
})
persis_info = add_unique_random_streams(persis_info, nworkers + 1)
exit_criteria = {'sim_max': budget, 'elapsed_wallclock_time': 300}
# Perform the run
H, persis_info, flag = libE(sim_specs,
gen_specs,
exit_criteria,
persis_info,
libE_specs=libE_specs)
if is_master:
assert flag == 0
assert len(H) >= budget
# Calculating the Jacobian at the best point (though this information was not used by pounders)
from libensemble.sim_funcs.chwirut1 import EvaluateJacobian
J = EvaluateJacobian(H['x'][np.argmin(H['f'])])
assert np.linalg.norm(J) < 2000
outname = os.path.splitext(__file__)[0] + '_sub_comm' + str(
sub_comm_number)
save_libE_output(H, persis_info, outname, nworkers)
