def test_gen_data_collector(self):
config = self.createTestPath("local/custom_kw/mini_config")
with ErtTestContext("python/enkf/export/gen_data_observation_collector", config) as context:
ert = context.getErt()
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(ert, "PERLIN", 1)
self.assertEqual(obs_key, "GEN_PERLIN_1")
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(ert, "PERLIN", 2)
self.assertEqual(obs_key, "GEN_PERLIN_2")
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(ert, "PERLIN", 3)
self.assertEqual(obs_key, "GEN_PERLIN_3")
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(ert, "PERLIN", 4)
self.assertIsNone(obs_key)
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(ert, "PERLINk", 1)
self.assertIsNone(obs_key)
data = GenDataObservationCollector.loadGenDataObservations(ert, "default", "GEN_PERLIN_1")
self.assertFloatEqual(data["GEN_PERLIN_1"][0], -0.616789)
self.assertFloatEqual(data["STD_GEN_PERLIN_1"][0], 0.2)
with self.assertRaises(KeyError):
GenDataObservationCollector.loadGenDataObservations(ert, "default", "GEN_PERLIN_4")
def gatherGenDataObservationData(ert, case, key_with_report_step):
""" :rtype: pandas.DataFrame """
key, report_step = key_with_report_step.split("@", 1)
report_step = int(report_step)
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(ert, key, report_step)
if obs_key is not None:
obs_data = GenDataObservationCollector.loadGenDataObservations(ert, case, [obs_key])
columns = {obs_key: key_with_report_step, "STD_%s" % obs_key: "STD_%s" % key_with_report_step}
obs_data = obs_data.rename(columns=columns)
else:
obs_data = DataFrame()
return obs_data.dropna()
def test_gen_data_collector(self):
config = self.createTestPath("local/custom_kw/mini_config")
with ErtTestContext(
"python/enkf/export/gen_data_observation_collector",
config) as context:
ert = context.getErt()
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(
ert, "PERLIN", 1)
self.assertEqual(obs_key, "GEN_PERLIN_1")
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(
ert, "PERLIN", 2)
self.assertEqual(obs_key, "GEN_PERLIN_2")
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(
ert, "PERLIN", 3)
self.assertEqual(obs_key, "GEN_PERLIN_3")
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(
ert, "PERLIN", 4)
self.assertIsNone(obs_key)
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(
ert, "PERLINk", 1)
self.assertIsNone(obs_key)
data = GenDataObservationCollector.loadGenDataObservations(
ert, "default", ["GEN_PERLIN_1", "GEN_PERLIN_3"])
self.assertFloatEqual(data["GEN_PERLIN_1"][0], -0.616789)
self.assertFloatEqual(data["STD_GEN_PERLIN_1"][0], 0.2)
with self.assertRaises(KeyError):
data["GEN_PERLIN_2"]
key, report_step = key.split("@", 1)
report_step = int(report_step)
try:
data = GenDataCollector.loadGenData(ert, case, key, report_step)
except ValueError:
data = DataFrame()
return data.dropna() # removes all rows that has a NaN
@staticmethod
def gatherGenDataObservationData(ert, case, key_with_report_step):
""" :rtype: pandas.DataFrame """
key, report_step = key_with_report_step.split("@", 1)
report_step = int(report_step)
obs_key = GenDataObservationCollector.getObservationKeyForDataKey(
ert, key, report_step)
if obs_key is not None:
obs_data = GenDataObservationCollector.loadGenDataObservations(
ert, case, obs_key)
columns = {
obs_key: key_with_report_step,
"STD_%s" % obs_key: "STD_%s" % key_with_report_step
}
obs_data = obs_data.rename(columns=columns)
else:
obs_data = DataFrame()
return obs_data.dropna()
@staticmethod