def test_summary_observation_collector(self):
with ErtTestContext("python/enkf/export/summary_observation_collector", self.config) as context:
ert = context.getErt()
self.assertTrue(SummaryObservationCollector.summaryKeyHasObservations(ert, "FOPR"))
self.assertFalse(SummaryObservationCollector.summaryKeyHasObservations(ert, "FOPT"))
keys = SummaryObservationCollector.getAllObservationKeys(ert)
self.assertTrue("FOPR" in keys)
self.assertTrue("WOPR:OP1" in keys)
self.assertFalse("WOPR:OP2" in keys)
data = SummaryObservationCollector.loadObservationData(ert, "default_0")
self.assertFloatEqual(data["FOPR"]["2010-01-10"], 0.001696887)
self.assertFloatEqual(data["STD_FOPR"]["2010-01-10"], 0.1)
self.assertFloatEqual(data["WOPR:OP1"]["2010-03-31"], 0.1)
self.assertFloatEqual(data["STD_WOPR:OP1"]["2010-03-31"], 0.05)
with self.assertRaises(KeyError):
fgir = data["FGIR"]
data = SummaryObservationCollector.loadObservationData(ert, "default_0", ["WOPR:OP1"])
self.assertFloatEqual(data["WOPR:OP1"]["2010-03-31"], 0.1)
self.assertFloatEqual(data["STD_WOPR:OP1"]["2010-03-31"], 0.05)
with self.assertRaises(KeyError):
data["FOPR"]
def test_summary_collector():
res_config = ResConfig("snake_oil.ert")
ert = EnKFMain(res_config)
summary = EclSum("refcase/SNAKE_OIL_FIELD.UNSMRY")
data = SummaryObservationCollector.loadObservationData(ert, "default_0")
assert (data["FOPR"].values.tolist() == summary.numpy_vector(
"FOPRH", report_only=True).tolist())
def test_ahmanalysis_run_field(test_data_root, grid_prop):
"""test data_set with scalar and Field parameters"""
test_data_dir = os.path.join(test_data_root, "snake_oil")
shutil.copytree(test_data_dir, "test_data")
os.chdir(os.path.join("test_data"))
os.makedirs("fields")
grid = EclGridGenerator.createRectangular((10, 12, 5), (1, 1, 1))
for iens in range(10):
grid_prop("PERMX", 10, grid.getGlobalSize(), "fields/permx%d.grdecl" % iens)
grid_prop("PORO", 0.2, grid.getGlobalSize(), "fields/poro%d.grdecl" % iens)
res_config = ResConfig("snake_oil_field.ert")
res_config.convertToCReference(None)
ert = EnKFMain(res_config)
ahmanalysis.AhmAnalysisJob(ert).run(prior_name="default")
# assert that this returns/generates the delta field parameter
gen_obs_list = GenDataObservationCollector.getAllObservationKeys(ert)
summary_obs_list = SummaryObservationCollector.getAllObservationKeys(ert)
obs_keys = gen_obs_list + summary_obs_list
output_deltafield = os.path.join(
"storage",
"snake_oil_field",
"reports",
"default",
"AhmAnalysisJob",
"delta_fieldPERMX.csv",
)
assert os.path.isfile(output_deltafield)
delta_df = pd.read_csv(output_deltafield, index_col=0)
assert len(delta_df.columns) == 8 + (len(obs_keys) * 2) + 1
# check field parameter is present and not empty in the final KS matrix
output_ks = output_deltafield.replace("delta_fieldPERMX.csv", "ks.csv")
ks_df = pd.read_csv(output_ks, index_col=0)
assert not ks_df.empty
assert "FIELD_PERMX" in ks_df.index.tolist()
check_empty = ks_df.loc[["FIELD_PERMX"], :].isnull().all(axis=1)
assert not check_empty["FIELD_PERMX"]
def load_observation_data(self, case_name, keys=None):
return SummaryObservationCollector.loadObservationData(
self._enkf_main, case_name, keys)
def gatherSummaryObservationData(ert, case, key):
if ert.getKeyManager().isKeyWithObservations(key):
return SummaryObservationCollector.loadObservationData(ert, case, [key]).dropna()
else:
return DataFrame()