def run(self, *args):
facade = LibresFacade(self.ert())
parser = spearman_job_parser()
args = parser.parse_args(args)
spearman_job(facade, args.threshold, args.dry_run)
def test_main_entry_point_gen_data(monkeypatch):
scal_job = Mock()
monkeypatch.setattr(spearman, "scaling_job", scal_job)
test_data_dir = os.path.join(TEST_DATA_DIR, "local", "snake_oil")
shutil.copytree(test_data_dir, "test_data")
os.chdir(os.path.join("test_data"))
res_config = ResConfig("snake_oil.ert")
ert = EnKFMain(res_config)
facade = LibresFacade(ert)
spearman.spearman_job(facade, 1.0, False)
assert scal_job.call_count == 71
def run(self, *args):
facade = LibresFacade(self.ert())
obs_keys = [
facade.get_observation_key(nr)
for nr, _ in enumerate(facade.get_observations())
]
measured_data = MeasuredData(facade, obs_keys)
parser = spearman_job_parser()
args = parser.parse_args(args)
scaling_configs = spearman_job(measured_data, args.threshold)
if not args.dry_run:
try:
CorrelatedObservationsScalingJob(
self.ert()).run(scaling_configs)
except EmptyDatasetException:
pass
def run(misfit_preprocessor_config, measured_data, reporter):
config = assemble_config(misfit_preprocessor_config, measured_data)
if not config.valid:
raise ValidationError("Invalid configuration of misfit preprocessor",
config.errors)
config = config.snapshot
if config.clustering.method == SPEARMAN_CORRELATION:
sconfig = config.clustering.spearman_correlation
scaling_configs = spearman_job(
measured_data,
sconfig.fcluster.t,
reporter,
criterion=sconfig.fcluster.criterion,
depth=sconfig.fcluster.depth,
method=sconfig.linkage.method,
metric=sconfig.linkage.metric,
)
else:
raise AssertionError("Unknown clustering method: {}".format(
config.clustering.method))
return scaling_configs