'components': m
}
}
alloc_specs = {
'alloc_f': give_sim_work_first, # Allocation function
'out': [('allocated', bool)], # Output fields (included in History)
'user': {
'stop_on_NaNs': True, # Should alloc preempt evals
'batch_mode': True, # Wait until all sim evals are done
'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,
'gen_f': gen_random_sample, # Our generator function
'out': [('x', float, (1, ))], # gen_f output (name, type, size).
'user': {
'lower': np.array([-3]), # random sampling lower bound
'upper': np.array([3]), # random sampling upper bound
'gen_batch_size': 5 # number of values gen_f will generate per call
}
}
sim_specs = {
'sim_f': sim_find_sine, # Our simulator function
'in': ['x'], # Input field names. 'x' from gen_f output
'out': [('y', float)]
} # sim_f output. 'y' = sine('x')
persis_info = add_unique_random_streams(
{}, nworkers + 1) # Intitialize manager/workers random streams
exit_criteria = {'sim_max': 80} # Stop libEnsemble after 80 simulations
H, persis_info, flag = libE(sim_specs,
gen_specs,
exit_criteria,
persis_info,
libE_specs=libE_specs)
# Some (optional) statements to visualize our History array
print([i for i in H.dtype.fields])
print(H)
colors = ['b', 'g', 'r', 'y', 'm', 'c', 'k', 'w']
