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Add RFT QC widget status column test #14355

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Merged
HakonSohoel merged 1 commit into from
Sep 8, 2026
+139 −1
Merged

Add RFT QC widget status column test #14355

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140 changes: 139 additions & 1 deletion tests/ert/unit_tests/gui/ertwidgets/test_rft_qc_widget.py
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Original file line number Diff line number Diff line change
Expand Up @@ -598,12 +598,26 @@ def _filter_values(list_widget) -> list[str]:
assert widget._file_responses.is_empty()


def _mock_rft_ensemble(stored_observations, stored_location_metadata, stored_responses):
def _mock_rft_ensemble(
stored_observations,
stored_location_metadata,
stored_responses,
*,
approximate_missing_values: bool = False,
):
ensemble = MagicMock()
experiment = MagicMock()
experiment.observations = (
{} if stored_observations is None else {"rft": stored_observations}
)
experiment.response_configuration = {
"rft": RFTConfig(
input_files=[],
data_to_read={}, # Read all available RFT data
zonemap=None,
approximate_missing_values=approximate_missing_values,
)
}
type(ensemble).experiment = PropertyMock(return_value=experiment)
if isinstance(stored_location_metadata, BaseException):
ensemble.load_observation_location_metadata.side_effect = (
Expand Down Expand Up @@ -915,6 +929,130 @@ def test_that_observations_status_column_is_added(qtbot):
]


@pytest.mark.parametrize(
("with_observations"),
[
pytest.param(
False,
id="no rft observations",
),
pytest.param(
True,
id="with rft observations",
),
],
)
@pytest.mark.parametrize(
("with_responses"),
[
pytest.param(
False,
id="no rft responses",
),
pytest.param(
True,
id="with rft responses",
),
],
)
@pytest.mark.parametrize(
("approximate_missing_values"),
[
pytest.param(
False,
id="approximate off",
),
pytest.param(
True,
id="approximate on",
),
],
)
def test_that_response_status_column_is_added(
qtbot,
with_observations,
with_responses,
approximate_missing_values,
):
# fmt: off
observations = [
# east north tvd zone observation
( 1.0, 1.0, 2.0, "zone1", 10.0), # ruff: ignore[whitespace-after-open-bracket, multiple-spaces-after-comma]
] if with_observations else []

metadata = [
# east north tvd actual_zones connection_cell cell_center
( 1.0, 1.0, 2.0, ["zone1"], [1, 1, 2], [1.0, 1.0, 2.0]), # ruff: ignore[whitespace-after-open-bracket, multiple-spaces-after-comma]
] if with_observations else []

responses = [
# connection_cell values cell_center depth cell_zones
( [1, 1, 1], 10.0, [1.0, 1.0, 1.0], 1.0, ["zone1"]), # ruff: ignore[whitespace-after-open-bracket, multiple-spaces-after-comma]
( [1, 1, 3], 12.0, [1.0, 1.0, 3.0], 3.0, ["zone1"]), # ruff: ignore[whitespace-after-open-bracket, multiple-spaces-after-comma]
] if with_responses else []
# fmt: on

if not with_responses:
expected_statuses = []
elif approximate_missing_values and with_observations:
expected_statuses = [_PointStatus.RESPONSE] * 2 + [_PointStatus.APPROXIMATED]
else:
expected_statuses = [_PointStatus.RESPONSE] * 2

stored_observations = pl.DataFrame(
observations,
schema={

@achaikou achaikou Sep 3, 2026

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Just a note:

To keep schemas consistent with possible future changes might be useful to use
defaults_generator's create_rft_observation + create_observation_dataframe's _handle_rft_observation (or just add new create_rft_observation_dataframe function to defaults_generator)

Also might be nice adding create_rft_response consistent with default rft observations (in the lines of create_seismic_response) to use standard response schema and get rid of explicitly defining uninteresting defaults like well-date-pressure.

"east": pl.Float32,
"north": pl.Float32,
"tvd": pl.Float32,
"zone": pl.String,
"observations": pl.Float32,
},
orient="row",
).with_columns(
pl.lit("WELL:2000-01-01:PRESSURE").alias("response_key"),
pl.lit("WELL").alias("well"),
pl.lit("2000-01-01").alias("date"),
pl.lit(5.0, dtype=pl.Float32).alias("std"),
)

stored_location_metadata = pl.DataFrame(
metadata,
schema=RFTConfig.location_metadata_schema(),
orient="row",
)

stored_responses = pl.DataFrame(
responses,
schema={
"well_connection_cell": pl.Array(pl.Int64, 3),
"values": pl.Float32,
"cell_center": pl.Array(pl.Float32, 3),
"depth": pl.Float32,
"cell_zones": pl.List(pl.String),
},
orient="row",
).with_columns(
pl.lit("WELL:2000-01-01:PRESSURE").alias("response_key"),
pl.lit("WELL").alias("well"),
pl.lit("2000-01-01").alias("date"),
pl.lit("PRESSURE").alias("property"),
)

ensemble = _mock_rft_ensemble(
stored_observations=stored_observations,
stored_location_metadata=stored_location_metadata,
stored_responses=stored_responses,
approximate_missing_values=approximate_missing_values,
)

widget = RftQcWidget()
qtbot.addWidget(widget)
widget.update_realization(ensemble, 0)

assert widget._responses["status"].to_list() == expected_statuses


def test_that_deduplicate_points_per_coordinate_and_status_keeps_one_point_per_coordinate_per_status(): # ruff: ignore[line-too-long]
# Every distinct status at a coordinate is kept, while duplicate rows sharing
# both coordinate and status collapse to a single point.
Expand Down
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