def test_ensemble_evaluator(tmpdir, source_root):
shutil.copytree(
os.path.join(source_root, "test-data", "local", "poly_example"),
os.path.join(str(tmpdir), "poly_example"),
)
with tmpdir.as_cwd():
parser = ArgumentParser(prog="test_main")
parsed = ert_parser(
parser,
[
ENSEMBLE_SMOOTHER_MODE,
"--target-case",
"poly_runpath_file",
"--realizations",
"1,2,4,8,16,32,64",
"--enable-ensemble-evaluator",
"poly_example/poly.ert",
],
)
FeatureToggling.update_from_args(parsed)
assert FeatureToggling.is_enabled("ensemble-evaluator") is True
run_cli(parsed)
FeatureToggling.reset()
def _runAndPostProcess(self, run_context, arguments, update_id=None):
phase_msg = "Running iteration %d of %d simulation iterations..." % (
run_context.get_iter(),
self.phaseCount() - 1,
)
self.setPhase(run_context.get_iter(), phase_msg, indeterminate=False)
self.setPhaseName("Pre processing...", indeterminate=True)
self.ert().getEnkfSimulationRunner().createRunPath(run_context)
EnkfSimulationRunner.runWorkflows(HookRuntime.PRE_SIMULATION,
ert=ERT.ert)
# create ensemble
ensemble_id = self._post_ensemble_data(update_id=update_id)
self.setPhaseName("Running forecast...", indeterminate=False)
if FeatureToggling.is_enabled("ensemble-evaluator"):
ee_config = arguments["ee_config"]
num_successful_realizations = self.run_ensemble_evaluator(
run_context, ee_config)
else:
self._job_queue = self._queue_config.create_job_queue()
num_successful_realizations = (
self.ert().getEnkfSimulationRunner().runSimpleStep(
self._job_queue, run_context))
self.checkHaveSufficientRealizations(num_successful_realizations)
self.setPhaseName("Post processing...", indeterminate=True)
EnkfSimulationRunner.runWorkflows(HookRuntime.POST_SIMULATION,
ert=ERT.ert)
self._post_ensemble_results(ensemble_id)
return ensemble_id
def _simulateAndPostProcess(self, run_context, arguments):
iteration = run_context.get_iter( )
phase_string = "Running simulation for iteration: %d" % iteration
self.setPhaseName(phase_string, indeterminate=True)
self.ert().getEnkfSimulationRunner().createRunPath(run_context)
phase_string = "Pre processing for iteration: %d" % iteration
self.setPhaseName(phase_string)
EnkfSimulationRunner.runWorkflows(HookRuntime.PRE_SIMULATION, ert=ERT.ert)
phase_string = "Running forecast for iteration: %d" % iteration
self.setPhaseName(phase_string, indeterminate=False)
if FeatureToggling.is_enabled("ensemble-evaluator"):
num_successful_realizations = self.run_ensemble_evaluator(run_context)
else:
self._job_queue = self._queue_config.create_job_queue()
num_successful_realizations = self.ert().getEnkfSimulationRunner().runSimpleStep(self._job_queue, run_context)
num_successful_realizations += arguments.get('prev_successful_realizations', 0)
self.checkHaveSufficientRealizations(num_successful_realizations)
phase_string = "Post processing for iteration: %d" % iteration
self.setPhaseName(phase_string, indeterminate=True)
EnkfSimulationRunner.runWorkflows(HookRuntime.POST_SIMULATION, ert=ERT.ert)
return num_successful_realizations
def start_ert_server(mode: str):
if mode in ("api", "vis") or not FeatureToggling.is_enabled("new-storage"):
yield
return
with Storage.start_server():
yield
def runSimulations__(self, arguments, run_msg):
run_context = self.create_context(arguments)
self.setPhase(0, "Running simulations...", indeterminate=False)
self.setPhaseName("Pre processing...", indeterminate=True)
self.ert().getEnkfSimulationRunner().createRunPath(run_context)
EnkfSimulationRunner.runWorkflows(HookRuntime.PRE_SIMULATION, ERT.ert)
self.setPhaseName(run_msg, indeterminate=False)
if FeatureToggling.is_enabled("ensemble-evaluator"):
num_successful_realizations = self.run_ensemble_evaluator(
run_context)
else:
self._job_queue = self._queue_config.create_job_queue()
num_successful_realizations = (
self.ert().getEnkfSimulationRunner().runEnsembleExperiment(
self._job_queue, run_context))
num_successful_realizations += arguments.get(
"prev_successful_realizations", 0)
self.checkHaveSufficientRealizations(num_successful_realizations)
self.setPhaseName("Post processing...", indeterminate=True)
EnkfSimulationRunner.runWorkflows(HookRuntime.POST_SIMULATION, ERT.ert)
self.setPhase(1, "Simulations completed.") # done...
dump_to_new_storage()
return run_context
def run_cli(args):
logging.basicConfig(level=logging.INFO, format="%(message)s")
res_config = ResConfig(args.config)
os.chdir(res_config.config_path)
ert = EnKFMain(res_config, strict=True, verbose=args.verbose)
notifier = ErtCliNotifier(ert, args.config)
ERT.adapt(notifier)
if args.mode == WORKFLOW_MODE:
execute_workflow(args.name)
return
model, argument = create_model(args)
# Test run does not have a current_case
if "current_case" in args and args.current_case:
ERT.enkf_facade.select_or_create_new_case(args.current_case)
if (
args.mode
in [ENSEMBLE_SMOOTHER_MODE, ITERATIVE_ENSEMBLE_SMOOTHER_MODE, ES_MDA_MODE]
and args.target_case == ERT.enkf_facade.get_current_case_name()
):
msg = (
"ERROR: Target file system and source file system can not be the same. "
"They were both: {}.".format(args.target_case)
)
_clear_and_exit(msg)
ee_config = None
if FeatureToggling.is_enabled("ensemble-evaluator"):
ee_config = EvaluatorServerConfig()
argument.update({"ee_config": ee_config})
thread = threading.Thread(
name="ert_cli_simulation_thread",
target=model.startSimulations,
args=(argument,),
)
thread.start()
tracker = create_tracker(model, detailed_interval=0, ee_config=ee_config)
out = open(os.devnull, "w") if args.disable_monitoring else sys.stdout
monitor = Monitor(out=out, color_always=args.color_always)
try:
monitor.monitor(tracker)
except (SystemExit, KeyboardInterrupt):
print("\nKilling simulations...")
tracker.request_termination()
if args.disable_monitoring:
out.close()
thread.join()
if model.hasRunFailed():
_clear_and_exit(1) # the monitor has already reported the error message
def __init__(self, config_file):
QWidget.__init__(self)
self._config_file = config_file
self._ee_config = None
if FeatureToggling.is_enabled("ensemble-evaluator"):
self._ee_config = EvaluatorServerConfig()
self.setObjectName("Simulation_panel")
layout = QVBoxLayout()
self._simulation_mode_combo = QComboBox()
self._simulation_mode_combo.setObjectName("Simulation_mode")
addHelpToWidget(self._simulation_mode_combo, "run/simulation_mode")
self._simulation_mode_combo.currentIndexChanged.connect(
self.toggleSimulationMode)
simulation_mode_layout = QHBoxLayout()
simulation_mode_layout.addSpacing(10)
simulation_mode_layout.addWidget(QLabel("Simulation mode:"), 0,
Qt.AlignVCenter)
simulation_mode_layout.addWidget(self._simulation_mode_combo, 0,
Qt.AlignVCenter)
simulation_mode_layout.addSpacing(20)
self.run_button = QToolButton()
self.run_button.setObjectName("start_simulation")
self.run_button.setIconSize(QSize(32, 32))
self.run_button.setText("Start Simulation")
self.run_button.setIcon(resourceIcon("ide/gear_in_play"))
self.run_button.clicked.connect(self.runSimulation)
self.run_button.setToolButtonStyle(Qt.ToolButtonTextBesideIcon)
addHelpToWidget(self.run_button, "run/start_simulation")
simulation_mode_layout.addWidget(self.run_button)
simulation_mode_layout.addStretch(1)
layout.addSpacing(5)
layout.addLayout(simulation_mode_layout)
layout.addSpacing(10)
self._simulation_stack = QStackedWidget()
self._simulation_stack.setLineWidth(1)
self._simulation_stack.setFrameStyle(QFrame.StyledPanel)
layout.addWidget(self._simulation_stack)
self._simulation_widgets = OrderedDict()
""" :type: OrderedDict[BaseRunModel,SimulationConfigPanel]"""
self.addSimulationConfigPanel(SingleTestRunPanel())
self.addSimulationConfigPanel(EnsembleExperimentPanel())
if ERT.ert.have_observations():
self.addSimulationConfigPanel(EnsembleSmootherPanel())
self.addSimulationConfigPanel(MultipleDataAssimilationPanel())
self.addSimulationConfigPanel(IteratedEnsembleSmootherPanel())
self.setLayout(layout)
def create_tracker(
model,
general_interval=5,
detailed_interval=10,
qtimer_cls=None,
event_handler=None,
num_realizations=None,
):
"""Creates a tracker tracking a @model. The provided model
is updated in two tiers: @general_interval, @detailed_interval.
Setting any interval to <=0 disables update.
Should a @qtimer_cls be defined, the Qt event loop will be used for
tracking. @event_handler must then be defined.
If @num_realizations is defined, then the intervals are scaled
according to some affine transformation such that it is tractable to
do tracking.
If @ee_host_port_tuple then the factory will produce something that can
track an ensemble evaluator.
"""
if num_realizations is not None:
general_interval, detailed_interval = scale_intervals(num_realizations)
ee_config = load_config()
ee_monitor_connection_details = (
(ee_config.get("host"), ee_config.get("port"))
if FeatureToggling.is_enabled("ensemble-evaluator")
else None
)
if qtimer_cls:
if not event_handler:
raise ValueError(
"event_handler must be defined if" + "qtimer_cls is defined"
)
return QTimerTracker(
model,
qtimer_cls,
general_interval,
detailed_interval,
event_handler,
ee_monitor_connection_details,
)
else:
return BlockingTracker(
model,
general_interval,
detailed_interval,
ee_monitor_connection_details,
)
def start_ert_server():
monitor = None
if FeatureToggling.is_enabled("new-storage"):
from ert_shared.storage.server_monitor import ServerMonitor
monitor = ServerMonitor.get_instance()
monitor.start()
try:
yield
finally:
if monitor is not None:
monitor.shutdown()
def _simulateAndPostProcess(self,
run_context,
arguments,
update_id: int = None):
iteration = run_context.get_iter()
phase_string = "Running simulation for iteration: %d" % iteration
self.setPhaseName(phase_string, indeterminate=True)
self.ert().getEnkfSimulationRunner().createRunPath(run_context)
phase_string = "Pre processing for iteration: %d" % iteration
self.setPhaseName(phase_string)
EnkfSimulationRunner.runWorkflows(HookRuntime.PRE_SIMULATION,
ert=ERT.ert)
# Push ensemble, parameters, observations to new storage
new_ensemble_id = post_ensemble_data(update_id=update_id,
ensemble_size=self._ensemble_size)
phase_string = "Running forecast for iteration: %d" % iteration
self.setPhaseName(phase_string, indeterminate=False)
if FeatureToggling.is_enabled("ensemble-evaluator"):
ee_config = arguments["ee_config"]
num_successful_realizations = self.run_ensemble_evaluator(
run_context, ee_config)
else:
self._job_queue = self._queue_config.create_job_queue()
num_successful_realizations = (
self.ert().getEnkfSimulationRunner().runSimpleStep(
self._job_queue, run_context))
# Push simulation results to storage
post_ensemble_results(new_ensemble_id)
num_successful_realizations += arguments.get(
"prev_successful_realizations", 0)
self.checkHaveSufficientRealizations(num_successful_realizations)
phase_string = "Post processing for iteration: %d" % iteration
self.setPhaseName(phase_string, indeterminate=True)
EnkfSimulationRunner.runWorkflows(HookRuntime.POST_SIMULATION,
ert=ERT.ert)
return num_successful_realizations, new_ensemble_id
def runSimulations__(self, arguments, run_msg):
run_context = self.create_context(arguments)
self.setPhase(0, "Running simulations...", indeterminate=False)
self.setPhaseName("Pre processing...", indeterminate=True)
self.ert().getEnkfSimulationRunner().createRunPath(run_context)
# Push ensemble, parameters, observations to new storage
ensemble_id = post_ensemble_data(ensemble_size=self._ensemble_size)
EnkfSimulationRunner.runWorkflows(HookRuntime.PRE_SIMULATION, ERT.ert)
self.setPhaseName(run_msg, indeterminate=False)
if FeatureToggling.is_enabled("ensemble-evaluator"):
ee_config = arguments["ee_config"]
num_successful_realizations = self.run_ensemble_evaluator(
run_context, ee_config
)
else:
self._job_queue = self._queue_config.create_job_queue()
num_successful_realizations = (
self.ert()
.getEnkfSimulationRunner()
.runEnsembleExperiment(self._job_queue, run_context)
)
num_successful_realizations += arguments.get("prev_successful_realizations", 0)
self.checkHaveSufficientRealizations(num_successful_realizations)
self.setPhaseName("Post processing...", indeterminate=True)
EnkfSimulationRunner.runWorkflows(HookRuntime.POST_SIMULATION, ERT.ert)
self.setPhase(1, "Simulations completed.") # done...
# Push simulation results to storage
post_ensemble_results(ensemble_id)
return run_context
def create_tracker(
model,
general_interval=5,
detailed_interval=10,
num_realizations=None,
ee_config=None,
):
"""Creates a tracker tracking a @model. The provided model
is updated either purely event-driven, or in two tiers: @general_interval,
@detailed_interval. Whether updates are continuous or periodic depends on
invocation. In the case of periodic updates, setting an interval to <=0
disables update.
If @num_realizations is defined, then the intervals are scaled
according to some affine transformation such that it is tractable to
do tracking. This only applies to periodic updates.
If @ee_host_port_tuple then the factory will produce something that can
track an ensemble evaluator and emit events appropriately.
"""
if num_realizations is not None:
general_interval, detailed_interval = scale_intervals(num_realizations)
if FeatureToggling.is_enabled("ensemble-evaluator"):
return EvaluatorTracker(
model,
ee_config.host,
ee_config.port,
general_interval,
detailed_interval,
token=ee_config.token,
cert=ee_config.cert,
)
return LegacyTracker(
model,
general_interval,
detailed_interval,
)
def run_gui(args):
app = QApplication(
[]) # Early so that QT is initialized before other imports
app.setWindowIcon(resourceIcon("application/window_icon_cutout"))
if FeatureToggling.is_enabled("prefect"):
ert_conf_path = os.path.abspath(args.config)[:-3] + "ert"
with open(ert_conf_path, "w") as f:
f.write("""QUEUE_SYSTEM LOCAL
QUEUE_OPTION LOCAL MAX_RUNNING 50
RUNPATH out/real_%d/iter_%d
NUM_REALIZATIONS 100
MIN_REALIZATIONS 1
""")
res_config = ResConfig(ert_conf_path)
else:
res_config = ResConfig(args.config)
os.chdir(res_config.config_path)
ert = EnKFMain(res_config, strict=True, verbose=args.verbose)
# window reference must be kept until app.exec returns
window = _start_window(ert, args)
return app.exec_()
def test_tracking(
experiment_folder,
cmd_line_arguments,
num_successful,
num_iters,
tmpdir,
source_root,
):
shutil.copytree(
os.path.join(source_root, "test-data", "local",
f"{experiment_folder}"),
os.path.join(str(tmpdir), f"{experiment_folder}"),
)
config_lines = [
"INSTALL_JOB poly_eval2 POLY_EVAL\n"
"SIMULATION_JOB poly_eval2\n"
]
with tmpdir.as_cwd():
with open(f"{experiment_folder}/poly.ert", "a") as fh:
fh.writelines(config_lines)
parser = ArgumentParser(prog="test_main")
parsed = ert_parser(
parser,
cmd_line_arguments,
)
FeatureToggling.update_from_args(parsed)
res_config = ResConfig(parsed.config)
os.chdir(res_config.config_path)
ert = EnKFMain(res_config, strict=True, verbose=parsed.verbose)
notifier = ErtCliNotifier(ert, parsed.config)
ERT.adapt(notifier)
model, argument = create_model(parsed)
ee_config = None
if FeatureToggling.is_enabled("ensemble-evaluator"):
ee_config = EvaluatorServerConfig()
argument.update({"ee_config": ee_config})
thread = threading.Thread(
name="ert_cli_simulation_thread",
target=model.startSimulations,
args=(argument, ),
)
thread.start()
tracker = create_tracker(model,
general_interval=1,
detailed_interval=2,
ee_config=ee_config)
snapshots = {}
for event in tracker.track():
if isinstance(event, FullSnapshotEvent):
snapshots[event.iteration] = event.snapshot
if isinstance(event, SnapshotUpdateEvent):
if event.partial_snapshot is not None:
snapshots[event.iteration].merge(
event.partial_snapshot.data())
if isinstance(event, EndEvent):
break
assert tracker._progress() == 1.0
assert len(snapshots) == num_iters
for iter_, snapshot in snapshots.items():
successful_reals = list(
filter(
lambda item: item[1].status == REALIZATION_STATE_FINISHED,
snapshot.get_reals().items(),
))
assert len(successful_reals) == num_successful
for real_id, real in successful_reals:
assert (real.status == REALIZATION_STATE_FINISHED
), f"iter:{iter_} real:{real_id} was not finished"
poly = real.steps["0"].jobs["0"]
poly2 = real.steps["0"].jobs["1"]
assert poly.name == "poly_eval"
assert (poly.status == JOB_STATE_FINISHED
), f"real {real_id}/{poly['name']} was not finished"
assert poly2.name == "poly_eval2"
assert (poly2.status == JOB_STATE_FINISHED
), f"real {real_id}/{poly['name']} was not finished"
def runSimulations(self, arguments):
prior_context = self.create_context(arguments)
self.checkMinimumActiveRealizations(prior_context)
self.setPhase(0, "Running simulations...", indeterminate=False)
# self.setAnalysisModule(arguments["analysis_module"])
self.setPhaseName("Pre processing...", indeterminate=True)
self.ert().getEnkfSimulationRunner().createRunPath(prior_context)
# Push ensemble, parameters, observations to new storage
ensemble_id = post_ensemble_data()
EnkfSimulationRunner.runWorkflows(HookRuntime.PRE_SIMULATION,
ert=ERT.ert)
self.setPhaseName("Running forecast...", indeterminate=False)
if FeatureToggling.is_enabled("ensemble-evaluator"):
ee_config = arguments["ee_config"]
num_successful_realizations = self.run_ensemble_evaluator(
prior_context, ee_config)
else:
self._job_queue = self._queue_config.create_job_queue()
num_successful_realizations = self.ert().getEnkfSimulationRunner(
).runSimpleStep(self._job_queue, prior_context)
self.checkHaveSufficientRealizations(num_successful_realizations)
self.setPhaseName("Post processing...", indeterminate=True)
EnkfSimulationRunner.runWorkflows(HookRuntime.POST_SIMULATION,
ert=ERT.ert)
self.setPhaseName("Analyzing...")
EnkfSimulationRunner.runWorkflows(HookRuntime.PRE_FIRST_UPDATE,
ert=ERT.ert)
EnkfSimulationRunner.runWorkflows(HookRuntime.PRE_UPDATE, ert=ERT.ert)
es_update = self.ert().getESUpdate()
success = es_update.smootherUpdate(prior_context)
if not success:
raise ErtRunError("Analysis of simulation failed!")
EnkfSimulationRunner.runWorkflows(HookRuntime.POST_UPDATE, ert=ERT.ert)
# Push simulation results to storage
post_ensemble_results(ensemble_id)
self.setPhase(1, "Running simulations...")
self.ert().getEnkfFsManager().switchFileSystem(
prior_context.get_target_fs())
self.setPhaseName("Pre processing...")
rerun_context = self.create_context(arguments,
prior_context=prior_context)
self.ert().getEnkfSimulationRunner().createRunPath(rerun_context)
# Push ensemble, parameters, observations to new storage
analysis_module_name = self.ert().analysisConfig().activeModuleName()
ensemble_id = post_ensemble_data((ensemble_id, analysis_module_name))
EnkfSimulationRunner.runWorkflows(HookRuntime.PRE_SIMULATION,
ert=ERT.ert)
self.setPhaseName("Running forecast...", indeterminate=False)
if FeatureToggling.is_enabled("ensemble-evaluator"):
ee_config = arguments["ee_config"]
num_successful_realizations = self.run_ensemble_evaluator(
rerun_context, ee_config)
else:
self._job_queue = self._queue_config.create_job_queue()
num_successful_realizations = self.ert().getEnkfSimulationRunner(
).runSimpleStep(self._job_queue, rerun_context)
self.checkHaveSufficientRealizations(num_successful_realizations)
self.setPhaseName("Post processing...", indeterminate=True)
EnkfSimulationRunner.runWorkflows(HookRuntime.POST_SIMULATION,
ert=ERT.ert)
self.setPhase(2, "Simulations completed.")
# Push simulation results to storage
post_ensemble_results(ensemble_id)
return prior_context
def test_tracking(
experiment_folder,
cmd_line_arguments,
num_successful,
num_iters,
assert_present_in_snapshot,
tmpdir,
source_root,
):
shutil.copytree(
os.path.join(source_root, "test-data", "local",
f"{experiment_folder}"),
os.path.join(str(tmpdir), f"{experiment_folder}"),
)
config_lines = [
"INSTALL_JOB poly_eval2 POLY_EVAL\n"
"SIMULATION_JOB poly_eval2\n"
]
with tmpdir.as_cwd():
with open(f"{experiment_folder}/poly.ert", "a") as fh:
fh.writelines(config_lines)
parser = ArgumentParser(prog="test_main")
parsed = ert_parser(
parser,
cmd_line_arguments,
)
FeatureToggling.update_from_args(parsed)
res_config = ResConfig(parsed.config)
os.chdir(res_config.config_path)
ert = EnKFMain(res_config, strict=True, verbose=parsed.verbose)
notifier = ErtCliNotifier(ert, parsed.config)
ERT.adapt(notifier)
model, argument = create_model(parsed)
ee_config = None
if FeatureToggling.is_enabled("ensemble-evaluator"):
ee_config = EvaluatorServerConfig()
argument.update({"ee_config": ee_config})
thread = threading.Thread(
name="ert_cli_simulation_thread",
target=model.start_simulations_thread,
args=(argument, ),
)
thread.start()
tracker = create_tracker(model,
general_interval=1,
detailed_interval=2,
ee_config=ee_config)
snapshots = {}
for event in tracker.track():
if isinstance(event, FullSnapshotEvent):
snapshots[event.iteration] = event.snapshot
if isinstance(event, SnapshotUpdateEvent):
if event.partial_snapshot is not None:
snapshots[event.iteration].merge(
event.partial_snapshot.data())
if isinstance(event, EndEvent):
pass
assert tracker._progress() == 1.0
assert len(snapshots) == num_iters
for iter_, snapshot in snapshots.items():
successful_reals = list(
filter(
lambda item: item[1].status == state.
REALIZATION_STATE_FINISHED,
snapshot.get_reals().items(),
))
assert len(successful_reals) == num_successful
for (
iter_expression,
snapshot_expression,
expected,
) in assert_present_in_snapshot:
for i, snapshot in snapshots.items():
if re.match(iter_expression, str(i)):
check_expression(
snapshot.to_dict(),
snapshot_expression,
expected,
f"Snapshot {i} did not match:\n",
)
thread.join()
def killAllSimulations(self) -> None:
if FeatureToggling.is_enabled("ensemble-evaluator"):
raise NotImplementedError(
"the ensemble evaluator does not implement killAllSimulations")
self._job_queue.kill_all_jobs()
def run_cli(args):
res_config = ResConfig(args.config)
# Create logger inside function to make sure all handlers have been added to the root-logger.
logger = logging.getLogger(__name__)
logger.info(
"Logging forward model jobs",
extra={
"workflow_jobs":
str(res_config.model_config.getForwardModel().joblist())
},
)
os.chdir(res_config.config_path)
ert = EnKFMain(res_config, strict=True, verbose=args.verbose)
notifier = ErtCliNotifier(ert, args.config)
with ERT.adapt(notifier):
if args.mode == WORKFLOW_MODE:
execute_workflow(args.name)
return
model, argument = create_model(args)
# Test run does not have a current_case
if "current_case" in args and args.current_case:
ERT.enkf_facade.select_or_create_new_case(args.current_case)
if (args.mode in [
ENSEMBLE_SMOOTHER_MODE, ITERATIVE_ENSEMBLE_SMOOTHER_MODE,
ES_MDA_MODE
] and args.target_case == ERT.enkf_facade.get_current_case_name()):
msg = (
"ERROR: Target file system and source file system can not be the same. "
"They were both: {}.".format(args.target_case))
raise ErtCliError(msg)
ee_config = None
if FeatureToggling.is_enabled("ensemble-evaluator"):
ee_config = EvaluatorServerConfig(
custom_port_range=args.port_range)
argument.update({"ee_config": ee_config})
thread = threading.Thread(
name="ert_cli_simulation_thread",
target=model.start_simulations_thread,
args=(argument, ),
)
thread.start()
tracker = create_tracker(model,
detailed_interval=0,
ee_config=ee_config)
out = open(os.devnull, "w") if args.disable_monitoring else sys.stderr
monitor = Monitor(out=out, color_always=args.color_always)
try:
monitor.monitor(tracker)
except (SystemExit, KeyboardInterrupt):
print("\nKilling simulations...")
tracker.request_termination()
if args.disable_monitoring:
out.close()
thread.join()
if model.hasRunFailed():
raise ErtCliError(model.getFailMessage())