def start(config):
_config = run.startup_sequence(config)
# SingleSampler hardcodes nworkers to 1 and ignores user input
nworkers = 1
runner = run.single_sampler(_config)
H, persis_info, _ = runner.run()
if _config.is_manager:
filename = os.path.splitext(config)[0]
history_file_name = "H_sample_" + filename + ".npy"
save_libE_output(H,
persis_info,
history_file_name,
nworkers,
mess='Ran start point')
def configuration(config):
_config = run.startup_sequence(config)
sampler_type = _config.options.NAME
try:
nworkers = _config.options.nworkers
except AttributeError:
# Sampler defaults to 1 worker if not set
nworkers = 1
runner = run.sample_modes[sampler_type](_config)
H, persis_info, _ = runner.run()
if _config.is_manager:
filename = os.path.splitext(config)[0]
history_file_name = "H_sample_" + filename + ".npy"
save_libE_output(H,
persis_info,
history_file_name,
nworkers,
mess='Sampler completed')
def configuration(config):
_config = run.startup_sequence(config)
software = _config.options.NAME
try:
nworkers = _config.options.nworkers
except AttributeError:
# Any method that doesn't allow user specification must use 2 workers
nworkers = 2
runner = run.run_modes[software](_config)
H, persis_info, _ = runner.run()
if _config.is_manager:
filename = os.path.splitext(config)[0]
history_file_name = "H_" + filename + ".npy"
save_libE_output(H,
persis_info,
history_file_name,
nworkers,
mess='Run completed')
if software in _final_result:
_final_result[software](H)
'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}
# 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)
