def test_dataframe_export_file_set_name(rmssetup, rmsglobalconfig, dataframe):
"""Export the dataframe to file with correct metadata and name."""
logger.info("Active folder is %s", rmssetup)
os.chdir(rmssetup)
edata = dataio.ExportData(
config=rmsglobalconfig) # read from global config
output = edata.export(dataframe, name="MyDataframe")
logger.info("Output is %s", output)
assert str(output) == str(
(edata._rootpath / "share/results/tables/mydataframe.csv").resolve())
metaout = dataio.read_metadata(output)
assert metaout["data"]["spec"]["columns"] == ["COL1", "COL2"]
def test_regsurf_aggregated_diffdata(fmurun_w_casemetadata, rmsglobalconfig, regsurf):
"""Test surfaces, where input is diffdata."""
logger.info("Active folder is %s", fmurun_w_casemetadata)
os.chdir(fmurun_w_casemetadata)
edata = dataio.ExportData(
config=rmsglobalconfig, # read from global config
)
aggs = []
# create "forward" files
for i in range(10):
use_regsurf = regsurf.copy()
use_regsurf.values += float(i)
expfile = edata.export(
use_regsurf,
name="mymap_" + str(i),
realization=i,
timedata=[[20300201], [19990204]],
)
aggs.append(expfile)
# next task is to do an aggradation, and now the metadata already exists
# per input element which shall be re-used
surfs = xtgeo.Surfaces()
metas = []
for mapfile in aggs:
surf = xtgeo.surface_from_file(mapfile)
meta = dataio.read_metadata(mapfile)
metas.append(meta)
surfs.append([surf])
aggregated = surfs.statistics()
logger.info("Aggr. mean is %s", aggregated["mean"].values.mean()) # shall be 1238.5
aggdata = dataio.AggregatedData(
configs=metas,
operation="mean",
name="myaggrd",
verbosity="INFO",
aggregation_id="789politipoliti",
)
newmeta = aggdata.generate_aggregation_metadata(aggregated["mean"])
logger.info("New metadata:\n%s", utils.prettyprint_dict(newmeta))
def test_pyarrow_export_file_set_name(rmssetup, rmsglobalconfig, arrowtable):
"""Export the arrow to file with correct metadata and name."""
logger.info("Active folder is %s", rmssetup)
os.chdir(rmssetup)
edata = dataio.ExportData(
config=rmsglobalconfig) # read from global config
if arrowtable: # is None if PyArrow package is not present
output = edata.export(arrowtable, name="MyArrowtable")
logger.info("Output is %s", output)
assert str(output) == str(
(edata._rootpath /
"share/results/tables/myarrowtable.arrow").resolve())
metaout = dataio.read_metadata(output)
assert metaout["data"]["spec"]["columns"] == ["COL1", "COL2"]
def test_regsurf_aggregated(fmurun_w_casemetadata, rmsglobalconfig, regsurf):
"""Test generating aggragated metadata for a surface, where input has metadata."""
logger.info("Active folder is %s", fmurun_w_casemetadata)
os.chdir(fmurun_w_casemetadata)
edata = dataio.ExportData(
config=rmsglobalconfig, # read from global config
verbosity="INFO",
)
aggs = []
# create "forward" files
for i in range(1): # TODO! 10
use_regsurf = regsurf.copy()
use_regsurf.values += float(i)
expfile = edata.export(use_regsurf, name="mymap_" + str(i), realization=i)
aggs.append(expfile)
# next task is to do an aggradation, and now the metadata already exists
# per input element which shall be re-used
surfs = xtgeo.Surfaces()
metas = []
for mapfile in aggs:
surf = xtgeo.surface_from_file(mapfile)
meta = dataio.read_metadata(mapfile)
print(utils.prettyprint_dict(meta))
metas.append(meta)
surfs.append([surf])
aggregated = surfs.statistics()
logger.info("Aggr. mean is %s", aggregated["mean"].values.mean()) # shall be 1238.5
aggdata = dataio.AggregatedData(
configs=metas,
operation="mean",
name="myaggrd",
verbosity="INFO",
aggregation_id="1234",
)
newmeta = aggdata.generate_aggregation_metadata(aggregated["mean"])
logger.debug("New metadata:\n%s", utils.prettyprint_dict(newmeta))
assert newmeta["fmu"]["aggregation"]["id"] == "1234"
# let aggregation input True generate hash
aggdata = dataio.AggregatedData(
configs=metas,
operation="mean",
name="myaggrd2",
verbosity="INFO",
aggregation_id=True,
)
newmeta = aggdata.generate_aggregation_metadata(aggregated["mean"])
logger.debug("New metadata:\n%s", utils.prettyprint_dict(newmeta))
assert newmeta["fmu"]["aggregation"]["id"] != "1234"
assert newmeta["fmu"]["aggregation"]["id"] is not True
# let aggregation input None generate a missing key
aggdata = dataio.AggregatedData(
configs=metas,
operation="mean",
name="myaggrd2",
verbosity="INFO",
aggregation_id=None,
)
newmeta = aggdata.generate_aggregation_metadata(aggregated["mean"])
logger.debug("New metadata:\n%s", utils.prettyprint_dict(newmeta))
assert "id" not in newmeta["fmu"]["aggregation"]