Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Backport make sure that migrations use correct dtypes #9399

Merged
merged 1 commit into from
Nov 29, 2024
Merged

Backport make sure that migrations use correct dtypes #9399

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
70 changes: 43 additions & 27 deletions src/ert/storage/migration/to8.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -22,30 +22,35 @@ def from_path(cls, path: Path) -> "ObservationDatasetInfo":
response_key = ds.attrs["response"]
response_type = "summary" if response_key == "summary" else "gen_data"

df = polars.from_pandas(ds.to_dataframe().dropna().reset_index())
df = polars.from_pandas(
ds.to_dataframe().dropna().reset_index(),
schema_overrides={
"report_step": polars.UInt16,
"index": polars.UInt16,
"observations": polars.Float32,
"std": polars.Float32,
}
if response_type == "gen_data"
else {
"time": polars.Datetime("ms"), # type: ignore
"observations": polars.Float32,
"std": polars.Float32,
},
)

df = df.with_columns(observation_key=polars.lit(observation_key))

primary_key = (
["time"] if response_type == "summary" else ["report_step", "index"]
)
if response_type == "summary":
df = df.rename({"name": "response_key"})
df = df.with_columns(polars.col("time").dt.cast_time_unit("ms"))

if response_type == "gen_data":
df = df.with_columns(
polars.col("report_step").cast(polars.UInt16),
polars.col("index").cast(polars.UInt16),
response_key=polars.lit(response_key),
)

df = df.with_columns(
[
polars.col("std").cast(polars.Float32),
polars.col("observations").cast(polars.Float32),
]
)

df = df[
["response_key", "observation_key", *primary_key, "observations", "std"]
]
Expand All @@ -71,27 +76,38 @@ def _migrate_responses_from_netcdf_to_parquet(path: Path) -> None:
real_dirs = [*ens.glob("realization-*")]

for real_dir in real_dirs:
for ds_name in ["gen_data", "summary"]:
if (real_dir / f"{ds_name}.nc").exists():
gen_data_ds = xr.open_dataset(
real_dir / f"{ds_name}.nc", engine="scipy"
for response_type, schema_overrides in [
(
"gen_data",
{
"realization": polars.UInt16,
"report_step": polars.UInt16,
"index": polars.UInt16,
"values": polars.Float32,
},
),
(
"summary",
{
"realization": polars.UInt16,
"time": polars.Datetime("ms"),
"values": polars.Float32,
},
),
]:
if (real_dir / f"{response_type}.nc").exists():
xr_ds = xr.open_dataset(
real_dir / f"{response_type}.nc",
engine="scipy",
)

pandas_df = gen_data_ds.to_dataframe().dropna().reset_index()
pandas_df = xr_ds.to_dataframe().dropna().reset_index()
polars_df = polars.from_pandas(
pandas_df,
schema_overrides={
"values": polars.Float32,
"realization": polars.UInt16,
},
schema_overrides=schema_overrides, # type: ignore
)
polars_df = polars_df.rename({"name": "response_key"})

if "time" in polars_df:
polars_df = polars_df.with_columns(
polars.col("time").dt.cast_time_unit("ms")
)

# Ensure "response_key" is the first column
polars_df = polars_df.select(
["response_key"]
Expand All @@ -101,9 +117,9 @@ def _migrate_responses_from_netcdf_to_parquet(path: Path) -> None:
if col != "response_key"
]
)
polars_df.write_parquet(real_dir / f"{ds_name}.parquet")
polars_df.write_parquet(real_dir / f"{response_type}.parquet")

os.remove(real_dir / f"{ds_name}.nc")
os.remove(real_dir / f"{response_type}.nc")


def _migrate_observations_to_grouped_parquet(path: Path) -> None:
Expand Down
96 changes: 96 additions & 0 deletions tests/ert/unit_tests/storage/test_storage_migration.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,9 +5,11 @@
from pathlib import Path

import numpy as np
import polars
import pytest
from packaging import version

from ert.analysis import ErtAnalysisError, smoother_update
from ert.config import ErtConfig
from ert.storage import open_storage
from ert.storage.local_storage import (
Expand Down Expand Up @@ -355,3 +357,97 @@ def test_that_migrate_blockfs_creates_backup_folder(tmp_path, caplog):
assert (
tmp_path / "storage" / "_blockfs_backup" / "ensembles" / "ens_dummy.txt"
).exists()


@pytest.mark.integration_test
@pytest.mark.usefixtures("copy_shared")
@pytest.mark.parametrize(
"ert_version",
[
"10.3.1",
"8.4.5",
"8.0.11",
"6.0.5",
"5.0.0",
],
)
def test_that_manual_update_from_migrated_storage_works(
tmp_path,
block_storage_path,
snapshot,
monkeypatch,
ert_version,
):
shutil.copytree(
block_storage_path / f"all_data_types/storage-{ert_version}",
tmp_path / "all_data_types" / f"storage-{ert_version}",
)
monkeypatch.chdir(tmp_path / "all_data_types")
ert_config = ErtConfig.with_plugins().from_file("config.ert")
local_storage_set_ert_config(ert_config)
# To make sure all tests run against the same snapshot
snapshot.snapshot_dir = snapshot.snapshot_dir.parent
with open_storage(f"storage-{ert_version}", "w") as storage:
experiments = list(storage.experiments)
assert len(experiments) == 1
experiment = experiments[0]
ensembles = list(experiment.ensembles)
assert len(ensembles) == 1
prior_ens = ensembles[0]

assert set(experiment.observations["gen_data"].schema.items()) == {
("index", polars.UInt16),
("observation_key", polars.String),
("observations", polars.Float32),
("report_step", polars.UInt16),
("response_key", polars.String),
("std", polars.Float32),
}

assert set(experiment.observations["summary"].schema.items()) == {
("observation_key", polars.String),
("observations", polars.Float32),
("response_key", polars.String),
("std", polars.Float32),
("time", polars.Datetime(time_unit="ms")),
}

prior_gendata = prior_ens.load_responses(
"gen_data", tuple(range(prior_ens.ensemble_size))
)
prior_smry = prior_ens.load_responses(
"summary", tuple(range(prior_ens.ensemble_size))
)

assert set(prior_gendata.schema.items()) == {
("response_key", polars.String),
("index", polars.UInt16),
("realization", polars.UInt16),
("report_step", polars.UInt16),
("values", polars.Float32),
}

assert set(prior_smry.schema.items()) == {
("response_key", polars.String),
("time", polars.Datetime(time_unit="ms")),
("realization", polars.UInt16),
("values", polars.Float32),
}

posterior_ens = storage.create_ensemble(
prior_ens.experiment_id,
ensemble_size=prior_ens.ensemble_size,
iteration=1,
name="posterior",
prior_ensemble=prior_ens,
)

with pytest.raises(
ErtAnalysisError, match="No active observations for update step"
):
smoother_update(
prior_ens,
posterior_ens,
list(experiment.observation_keys),
list(ert_config.ensemble_config.parameters),
)